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Brener SA, Frankenhuis WE, Young ES, Ellis BJ. Social Class, Sex, and the Ability to Recognize Emotions: The Main Effect is in the Interaction. PERSONALITY AND SOCIAL PSYCHOLOGY BULLETIN 2024; 50:1197-1210. [PMID: 37013847 DOI: 10.1177/01461672231159775] [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] [Indexed: 04/05/2023]
Abstract
Previous research has demonstrated an inverse relation between subjective social class (SSC) and performance on emotion recognition tasks. Study 1 (N = 418) involved a preregistered replication of this effect using the Reading the Mind in the Eyes Task and the Cambridge Mindreading Face-Voice Battery. The inverse relation replicated; however, exploratory analyses revealed a significant interaction between sex and SSC in predicting emotion recognition, indicating that the effect was driven by males. In Study 2 (N = 745), we preregistered and tested the interaction on a separate archival dataset. The interaction replicated; the association between SSC and emotion recognition again occurred only in males. Exploratory analyses (Study 3; N = 381) examined the generalizability of the interaction to incidental face memory. Our results underscore the need to reevaluate previous research establishing the main effects of social class and sex on emotion recognition abilities, as these effects apparently moderate each other.
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Affiliation(s)
| | - Willem E Frankenhuis
- Utrecht University, The Netherlands
- Max Planck Institute for the Study of Crime, Security and Law, Freiburg, Germany
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2
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Herlin B, Uszynski I, Chauvel M, Dupont S, Poupon C. Sex-related variability of white matter tracts in the whole HCP cohort. Brain Struct Funct 2024:10.1007/s00429-024-02833-0. [PMID: 39012482 DOI: 10.1007/s00429-024-02833-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Accepted: 07/06/2024] [Indexed: 07/17/2024]
Abstract
Behavioral differences between men and women have been studied extensively, as have differences in brain anatomy. However, most studies have focused on differences in gray matter, while white matter has been much less studied. We conducted a comprehensive study of 77 deep white matter tracts to analyze their volumetric and microstructural variability between men and women in the full Human Connectome Project (HCP) cohort of 1065 healthy individuals aged 22-35 years. We found a significant difference in total brain volume between men and women (+ 12.6% in men), consistent with the literature. 16 tracts showed significant volumetric differences between men and women, one of which stood out due to a larger effect size: the corpus callosum genu, which was larger in women (+ 7.3% in women, p = 5.76 × 10-19). In addition, we found several differences in microstructural parameters between men and women, both using standard Diffusion Tensor Imaging (DTI) parameters and more complex microstructural parameters from the Neurite Orientation Dispersion and Density Imaging (NODDI) model, with the tracts showing the greatest differences belonging to motor (cortico-spinal tracts, cortico-cerebellar tracts) or limbic (cingulum, fornix, thalamo-temporal radiations) systems. These microstructural differences may be related to known behavioral differences between the sexes in timed motor performance, aggressiveness/impulsivity, and social cognition.
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Affiliation(s)
- B Herlin
- BAOBAB, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-Sur-Yvette, France.
- Rehabilitation Unit, AP-HP, Pitié-Salpêtrière Hospital, Paris, France.
- Université Paris Sorbonne, Paris, France.
| | - I Uszynski
- BAOBAB, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-Sur-Yvette, France
| | - M Chauvel
- BAOBAB, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-Sur-Yvette, France
| | - S Dupont
- Reference Center for Rare Epilepsies, Department of Neurology, Epileptology Unit, AP-HP, Pitié-Salpêtrière Hospital, Paris, France
- Rehabilitation Unit, AP-HP, Pitié-Salpêtrière Hospital, Paris, France
- Paris Brain Institute (ICM), Sorbonne-Université, Inserm U1127, CNRS 7225, Paris, France
- Université Paris Sorbonne, Paris, France
| | - C Poupon
- BAOBAB, NeuroSpin, Université Paris-Saclay, CNRS, CEA, Gif-Sur-Yvette, France
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Gu Y, Maria-Stauffer E, Bedford SA, Romero-Garcia R, Grove J, Børglum AD, Martin H, Baron-Cohen S, Bethlehem RA, Warrier V. Polygenic scores for autism are associated with neurite density in adults and children from the general population. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.10.24305539. [PMID: 38645251 PMCID: PMC11030520 DOI: 10.1101/2024.04.10.24305539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Genetic variants linked to autism are thought to change cognition and behaviour by altering the structure and function of the brain. Although a substantial body of literature has identified structural brain differences in autism, it is unknown whether autism-associated common genetic variants are linked to changes in cortical macro- and micro-structure. We investigated this using neuroimaging and genetic data from adults (UK Biobank, N = 31,748) and children (ABCD, N = 4,928). Using polygenic scores and genetic correlations we observe a robust negative association between common variants for autism and a magnetic resonance imaging derived phenotype for neurite density (intracellular volume fraction) in the general population. This result is consistent across both children and adults, in both the cortex and in white matter tracts, and confirmed using polygenic scores and genetic correlations. There were no sex differences in this association. Mendelian randomisation analyses provide no evidence for a causal relationship between autism and intracellular volume fraction, although this should be revisited using better powered instruments. Overall, this study provides evidence for shared common variant genetics between autism and cortical neurite density.
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Affiliation(s)
- Yuanjun Gu
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, UK
| | | | - Saashi A. Bedford
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, UK
| | | | | | - Rafael Romero-Garcia
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH
- Department of Medical Physiology and Biophysics, Instituto de Biomedicina de Sevilla (IBiS), HUVR/CSIC/Universidad de Sevilla/CIBERSAM, ISCIII, 41013, Sevilla, Spain, 41013
| | - Jakob Grove
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, 8210, Denmark
- Center for Genomics and Personalized Medicine (CGPM), Aarhus University, Aarhus, 8000, Denmark
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, Aarhus, 8000, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark, 8000
| | - Anders D. Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, 8210, Denmark
- Center for Genomics and Personalized Medicine (CGPM), Aarhus University, Aarhus, 8000, Denmark
- Department of Biomedicine (Human Genetics) and iSEQ Center, Aarhus University, Aarhus, 8000, Denmark
| | - Hilary Martin
- Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH, UK
- Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, UK
| | | | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 8AH
- Human Genetics Programme, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK
- Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, UK
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Abulseoud OA, Caparelli EC, Krell‐Roesch J, Geda YE, Ross TJ, Yang Y. Sex-difference in the association between social drinking, structural brain aging and cognitive function in older individuals free of cognitive impairment. Front Psychiatry 2024; 15:1235171. [PMID: 38651011 PMCID: PMC11033502 DOI: 10.3389/fpsyt.2024.1235171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 03/19/2024] [Indexed: 04/25/2024] Open
Abstract
Background We investigated a potential sex difference in the relationship between alcohol consumption, brain age gap and cognitive function in older adults without cognitive impairment from the population-based Mayo Clinic Study of Aging. Methods Self-reported alcohol consumption was collected using the food-frequency questionnaire. A battery of cognitive testing assessed performance in four different domains: attention, memory, language, and visuospatial. Brain magnetic resonance imaging (MRI) was conducted using 3-T scanners (Signa; GE Healthcare). Brain age was estimated using the Brain-Age Regression Analysis and Computational Utility Software (BARACUS). We calculated the brain age gap as the difference between predicted brain age and chronological age. Results The sample consisted of 269 participants [55% men (n=148) and 45% women (n=121) with a mean age of 79.2 ± 4.6 and 79.5 ± 4.7 years respectively]. Women had significantly better performance compared to men in memory, (1.12 ± 0.87 vs 0.57 ± 0.89, P<0.0001) language (0.66 ± 0.8 vs 0.33 ± 0.72, P=0.0006) and attention (0.79 ± 0.87 vs 0.39 ± 0.83, P=0.0002) z-scores. Men scored higher in visuospatial skills (0.71 ± 0.91 vs 0.44 ± 0.90, P=0.016). Compared to participants who reported zero alcohol drinking (n=121), those who reported alcohol consumption over the year prior to study enrollment (n=148) scored significantly higher in all four cognitive domains [memory: F3,268 = 5.257, P=0.002, Language: F3,258 = 12.047, P<0.001, Attention: F3,260 = 22.036, P<0.001, and Visuospatial: F3,261 = 9.326, P<0.001] after correcting for age and years of education. In addition, we found a significant positive correlation between alcohol consumption and the brain age gap (P=0.03). Post hoc regression analysis for each sex with language z-score revealed a significant negative correlation between brain age gap and language z-scores in women only (P=0.008). Conclusion Among older adults who report alcohol drinking, there is a positive association between higher average daily alcohol consumption and accelerated brain aging despite the fact that drinkers had better cognitive performance compared to zero drinkers. In women only, accelerated brain aging is associated with worse performance in language cognitive domain. Older adult women seem to be vulnerable to the negative effects of alcohol on brain structure and on certain cognitive functions.
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Affiliation(s)
- Osama A. Abulseoud
- Department of Psychiatry and Psychology, Mayo Clinic, Phoenix, AZ, United States
- Department of Neuroscience, Graduate School of Biomedical Sciences, Mayo Clinic College of Medicine, Phoenix, AZ, United States
| | - Elisabeth C. Caparelli
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
| | - Janina Krell‐Roesch
- Department of Quantitative Health Sciences, Mayo Clinic Rochester, Rochester, MN, United States
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Yonas E. Geda
- Department of Neurology, and the Franke Barrow Global Neuroscience Education Center, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Thomas J. Ross
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
| | - Yihong Yang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
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Torgerson C, Ahmadi H, Choupan J, Fan CC, Blosnich JR, Herting MM. Sex, gender diversity, and brain structure in early adolescence. Hum Brain Mapp 2024; 45:e26671. [PMID: 38590252 PMCID: PMC11002534 DOI: 10.1002/hbm.26671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 02/27/2024] [Accepted: 03/13/2024] [Indexed: 04/10/2024] Open
Abstract
There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.
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Affiliation(s)
- Carinna Torgerson
- Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
- Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Hedyeh Ahmadi
- Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Jeiran Choupan
- Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Chun Chieh Fan
- Center for Population Neuroscience and GeneticsLaureate Institute for Brain ResearchTulsaOklahomaUSA
- Department of Radiology, School of MedicineUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - John R. Blosnich
- Suzanne Dworak‐Peck School of Social WorkUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Megan M. Herting
- Department of Population and Public Health SciencesUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
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6
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Vosberg DE. Sex and Gender in Population Neuroscience. Curr Top Behav Neurosci 2024. [PMID: 38509404 DOI: 10.1007/7854_2024_468] [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: 03/22/2024]
Abstract
To understand psychiatric and neurological disorders and the structural and functional properties of the human brain, it is essential to consider the roles of sex and gender. In this chapter, I first define sex and gender and describe studies of sex differences in non-human animals. In humans, I describe the sex differences in behavioral and clinical phenotypes and neuroimaging-derived phenotypes, including whole-brain measures, regional subcortical and cortical measures, and structural and functional connectivity. Although structural whole-brain sex differences are large, regional effects (adjusting for whole-brain volumes) are typically much smaller and often fail to replicate. Nevertheless, while an individual neuroimaging feature may have a small effect size, aggregating them in a "maleness/femaleness" score or machine learning multivariate paradigm may prove to be predictive and informative of sex- and gender-related traits. Finally, I conclude by summarizing emerging investigations of gender norms and gender identity and provide methodological recommendations to incorporate sex and gender in population neuroscience research.
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Affiliation(s)
- Daniel E Vosberg
- Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, QC, Canada.
- Department of Neuroscience, Faculty of Medicine, University of Montreal, Montreal, QC, Canada.
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Lorenzetti V, Gaillard A, McTavish E, Grace S, Rossetti MG, Batalla A, Bellani M, Brambilla P, Chye Y, Conrod P, Cousijn J, Labuschagne I, Clemente A, Mackey S, Rendell P, Solowij N, Suo C, Li CSR, Terrett G, Thompson PM, Yücel M, Garavan H, Roberts CA. Cannabis Dependence is Associated with Reduced Hippocampal Subregion Volumes Independently of Sex: Findings from an ENIGMA Addiction Working Group Multi-Country Study. Cannabis Cannabinoid Res 2024. [PMID: 38498015 DOI: 10.1089/can.2023.0204] [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: 03/19/2024] Open
Abstract
Background: Males and females who consume cannabis can experience different mental health and cognitive problems. Neuroscientific theories of addiction postulate that dependence is underscored by neuroadaptations, but do not account for the contribution of distinct sexes. Further, there is little evidence for sex differences in the neurobiology of cannabis dependence as most neuroimaging studies have been conducted in largely male samples in which cannabis dependence, as opposed to use, is often not ascertained. Methods: We examined subregional hippocampus and amygdala volumetry in a sample of 206 people recruited from the ENIGMA Addiction Working Group. They included 59 people with cannabis dependence (17 females), 49 cannabis users without cannabis dependence (20 females), and 98 controls (33 females). Results: We found no group-by-sex effect on subregional volumetry. The left hippocampal cornu ammonis subfield 1 (CA1) volumes were lower in dependent cannabis users compared with non-dependent cannabis users (p<0.001, d=0.32) and with controls (p=0.022, d=0.18). Further, the left cornu ammonis subfield 3 (CA3) and left dentate gyrus volumes were lower in dependent versus non-dependent cannabis users but not versus controls (p=0.002, d=0.37, and p=0.002, d=0.31, respectively). All models controlled for age, intelligence quotient (IQ), alcohol and tobacco use, and intracranial volume. Amygdala volumetry was not affected by group or group-by-sex, but was smaller in females than males. Conclusions: Our findings suggest that the relationship between cannabis dependence and subregional volumetry was not moderated by sex. Specifically, dependent (rather than non-dependent) cannabis use may be associated with alterations in selected hippocampus subfields high in cannabinoid type 1 (CB1) receptors and implicated in addictive behavior. As these data are cross-sectional, it is plausible that differences predate cannabis dependence onset and contribute to the initiation of cannabis dependence. Longitudinal neuroimaging work is required to examine the time-course of the onset of subregional hippocampal alterations in cannabis dependence, and their progression as cannabis dependence exacerbates or recovers over time.
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Affiliation(s)
- Valentina Lorenzetti
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
| | - Alexandra Gaillard
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
- Centre for Mental Health and Department of Health Sciences and Biostatistics, Swinburne University, Hawthorn, Australia
| | - Eugene McTavish
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
| | - Sally Grace
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
| | - Maria Gloria Rossetti
- UOC Psichiatria, Azienda Ospedaliera Universitaria Integrata (AOUI), Verona, Italy
- Section of Psychiatry, Department of Neuroscience, Biomedicine and Movement Science, University of Verona, Verona, Italy
| | - Albert Batalla
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Marcella Bellani
- Section of Psychiatry, Department of Neuroscience, Biomedicine and Movement Science, University of Verona, Verona, Italy
| | - Paolo Brambilla
- UOC Psichiatria, Azienda Ospedaliera Universitaria Integrata (AOUI), Verona, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Yann Chye
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia
| | - Patricia Conrod
- Department of Psychiatry, Université de Montreal, CHU Ste Justine Hospital, Montreal, Canada
| | - Janna Cousijn
- Neuroscience of Addiction Lab, Center for Substance Use and Addiction Research (CESAR), Department of Psychology, Education & Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Izelle Labuschagne
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
- School of Psychology, Faculty of Health and Behavioural Sciences, University of Queensland, St Lucia, Australia
| | - Adam Clemente
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
| | - Scott Mackey
- Department of Psychiatry, University of Vermont, Burlington, Vermont, USA
| | - Peter Rendell
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
- School of Psychology, Faculty of Health and Behavioural Sciences, University of Queensland, St Lucia, Australia
| | - Nadia Solowij
- School of Psychology, Faculty of the Arts, Social Sciences and Humanities, University of Wollongong, Wollongong, Australia
| | - Chao Suo
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Gill Terrett
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
| | - Paul M Thompson
- Department of Neurology, Imaging Genetics Center, Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Murat Yücel
- QIMR Berghofer Medical Research Institute, Herston, Australia
| | - Hugh Garavan
- School of Psychology, Faculty of Health and Behavioural Sciences, University of Queensland, St Lucia, Australia
| | - Carl A Roberts
- Department of Psychology, Institute of Population Health, University of Liverpool, Liverpool, United Kingdom
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Guma E, Beauchamp A, Liu S, Levitis E, Ellegood J, Pham L, Mars RB, Raznahan A, Lerch JP. Comparative neuroimaging of sex differences in human and mouse brain anatomy. eLife 2024; 13:RP92200. [PMID: 38488854 PMCID: PMC10942785 DOI: 10.7554/elife.92200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2024] Open
Abstract
In vivo neuroimaging studies have established several reproducible volumetric sex differences in the human brain, but the causes of such differences are hard to parse. While mouse models are useful for understanding the cellular and mechanistic bases of sex-specific brain development, there have been no attempts to formally compare human and mouse neuroanatomical sex differences to ascertain how well they translate. Addressing this question would shed critical light on the use of the mouse as a translational model for sex differences in the human brain and provide insights into the degree to which sex differences in brain volume are conserved across mammals. Here, we use structural magnetic resonance imaging to conduct the first comparative neuroimaging study of sex-specific neuroanatomy of the human and mouse brain. In line with previous findings, we observe that in humans, males have significantly larger and more variable total brain volume; these sex differences are not mirrored in mice. After controlling for total brain volume, we observe modest cross-species congruence in the volumetric effect size of sex across 60 homologous regions (r=0.30). This cross-species congruence is greater in the cortex (r=0.33) than non-cortex (r=0.16). By incorporating regional measures of gene expression in both species, we reveal that cortical regions with greater cross-species congruence in volumetric sex differences also show greater cross-species congruence in the expression profile of 2835 homologous genes. This phenomenon differentiates primary sensory regions with high congruence of sex effects and gene expression from limbic cortices where congruence in both these features was weaker between species. These findings help identify aspects of sex-biased brain anatomy present in mice that are retained, lost, or inverted in humans. More broadly, our work provides an empirical basis for targeting mechanistic studies of sex-specific brain development in mice to brain regions that best echo sex-specific brain development in humans.
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Affiliation(s)
- Elisa Guma
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Antoine Beauchamp
- Mouse Imaging CentreTorontoCanada
- The Hospital for Sick ChildrenTorontoCanada
- Department of Medical Biophysics, University of TorontoTorontoCanada
| | - Siyuan Liu
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Elizabeth Levitis
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Jacob Ellegood
- Mouse Imaging CentreTorontoCanada
- The Hospital for Sick ChildrenTorontoCanada
| | - Linh Pham
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical 15 Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical 15 Neurosciences, University of OxfordOxfordUnited Kingdom
- Donders Institute for Brain, Cognition and Behaviour, Radboud University NijmegenNijmegenNetherlands
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Jason P Lerch
- Mouse Imaging CentreTorontoCanada
- The Hospital for Sick ChildrenTorontoCanada
- Department of Medical Biophysics, University of TorontoTorontoCanada
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical 15 Neurosciences, University of OxfordOxfordUnited Kingdom
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9
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Kirby ED, Andrushko JW, Rinat S, D'Arcy RCN, Boyd LA. Investigating female versus male differences in white matter neuroplasticity associated with complex visuo-motor learning. Sci Rep 2024; 14:5951. [PMID: 38467763 PMCID: PMC10928090 DOI: 10.1038/s41598-024-56453-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 03/06/2024] [Indexed: 03/13/2024] Open
Abstract
Magnetic resonance imaging (MRI) has increasingly been used to characterize structure-function relationships during white matter neuroplasticity. Biological sex differences may be an important factor that affects patterns of neuroplasticity, and therefore impacts learning and rehabilitation. The current study examined a participant cohort before and after visuo-motor training to characterize sex differences in microstructural measures. The participants (N = 27) completed a 10-session (4 week) complex visuo-motor training task with their non-dominant hand. All participants significantly improved movement speed and their movement speed variability over the training period. White matter neuroplasticity in females and males was examined using fractional anisotropy (FA) and myelin water fraction (MWF) along the cortico-spinal tract (CST) and the corpus callosum (CC). FA values showed significant differences in the middle portion of the CST tract (nodes 38-51) across the training period. MWF showed a similar cluster in the inferior portion of the tract (nodes 18-29) but did not reach significance. Additionally, at baseline, males showed significantly higher levels of MWF measures in the middle body of the CC. Combining data from females and males would have resulted in reduced sensitivity, making it harder to detect differences in neuroplasticity. These findings offer initial insights into possible female versus male differences in white matter neuroplasticity during motor learning. This warrants investigations into specific patterns of white matter neuroplasticity for females versus males across the lifespan. Understanding biological sex-specific differences in white matter neuroplasticity may have significant implications for the interpretation of change associated with learning or rehabilitation.
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Affiliation(s)
- Eric D Kirby
- BrainNet, Health and Technology District, Vancouver, BC, Canada
- Faculty of Individualized Interdisciplinary Studies, Simon Fraser University, Burnaby, BC, Canada
- Faculty of Science, Simon Fraser University, Burnaby, BC, Canada
| | - Justin W Andrushko
- DM Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, Canada
- Department of Sport, Exercise and Rehabilitation, Faculty of Health and Life Sciences, Northumbria University, Newcastle Upon Tyne, UK
- Brain Behaviour Laboratory, Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Shie Rinat
- Brain Behaviour Laboratory, Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Ryan C N D'Arcy
- BrainNet, Health and Technology District, Vancouver, BC, Canada.
- DM Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, Canada.
- Faculty of Applied Sciences, Simon Fraser University, Burnaby, BC, Canada.
| | - Lara A Boyd
- DM Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, Canada.
- Brain Behaviour Laboratory, Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, Canada.
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10
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Wierenga LM, Ruigrok A, Aksnes ER, Barth C, Beck D, Burke S, Crestol A, van Drunen L, Ferrara M, Galea LAM, Goddings AL, Hausmann M, Homanen I, Klinge I, de Lange AM, Geelhoed-Ouwerkerk L, van der Miesen A, Proppert R, Rieble C, Tamnes CK, Bos MGN. Recommendations for a Better Understanding of Sex and Gender in the Neuroscience of Mental Health. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:100283. [PMID: 38312851 PMCID: PMC10837069 DOI: 10.1016/j.bpsgos.2023.100283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 11/16/2023] [Accepted: 11/17/2023] [Indexed: 02/06/2024] Open
Abstract
There are prominent sex/gender differences in the prevalence, expression, and life span course of mental health and neurodiverse conditions. However, the underlying sex- and gender-related mechanisms and their interactions are still not fully understood. This lack of knowledge has harmful consequences for those with mental health problems. Therefore, we set up a cocreation session in a 1-week workshop with a multidisciplinary team of 25 researchers, clinicians, and policy makers to identify the main barriers in sex and gender research in the neuroscience of mental health. Based on this work, here we provide recommendations for methodologies, translational research, and stakeholder involvement. These include guidelines for recording, reporting, analysis beyond binary groups, and open science. Improved understanding of sex- and gender-related mechanisms in neuroscience may benefit public health because this is an important step toward precision medicine and may function as an archetype for studying diversity.
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Affiliation(s)
- Lara Marise Wierenga
- Institute of Psychology, Leiden University, Leiden, the Netherlands
- Leiden Institute for Brain and Cognition, Leiden University, Leiden, the Netherlands
| | - Amber Ruigrok
- Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Eira Ranheim Aksnes
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Claudia Barth
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dani Beck
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Sarah Burke
- Interdisciplinary Center for Psychopathology and Emotion regulation, Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Arielle Crestol
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lina van Drunen
- Institute of Psychology, Leiden University, Leiden, the Netherlands
- Leiden Institute for Brain and Cognition, Leiden University, Leiden, the Netherlands
| | - Maria Ferrara
- Department of Neuroscience and Rehabilitation, Institute of Psychiatry, University of Ferrara, Ferrara, Italy
- University Hospital Psychiatry Unit, Integrated Department of Mental Health and Addictive Behavior, University S. Anna Hospital and Health Trust, Ferrara, Italy
| | - Liisa Ann Margaret Galea
- Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Anne-Lise Goddings
- University College London Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Markus Hausmann
- Department of Psychology, Durham University, Durham, United Kingdom
| | - Inka Homanen
- Institute of Psychology, Leiden University, Leiden, the Netherlands
- Leiden Institute for Brain and Cognition, Leiden University, Leiden, the Netherlands
| | - Ineke Klinge
- Dutch Society for Gender & Health, the Netherlands
- Gendered Innovations at European Commission, Brussels, Belgium
| | - Ann-Marie de Lange
- Laboratory for Research in Neuroimaging, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Lineke Geelhoed-Ouwerkerk
- Institute of Psychology, Leiden University, Leiden, the Netherlands
- Leiden Institute for Brain and Cognition, Leiden University, Leiden, the Netherlands
| | - Anna van der Miesen
- Department of Child and Adolescent Psychiatry, Center of Expertise on Gender Dysphoria, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Ricarda Proppert
- Department of Clinical Psychology, Leiden University, Leiden, the Netherlands
| | - Carlotta Rieble
- Department of Clinical Psychology, Leiden University, Leiden, the Netherlands
| | - Christian Krog Tamnes
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Marieke Geerte Nynke Bos
- Institute of Psychology, Leiden University, Leiden, the Netherlands
- Leiden Institute for Brain and Cognition, Leiden University, Leiden, the Netherlands
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11
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Weller S, Derntl B, Plewnia C. Sex matters for the enhancement of cognitive training with transcranial direct current stimulation (tDCS). Biol Sex Differ 2023; 14:78. [PMID: 37919761 PMCID: PMC10623760 DOI: 10.1186/s13293-023-00561-4] [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: 07/17/2023] [Accepted: 10/16/2023] [Indexed: 11/04/2023] Open
Abstract
BACKGROUND Transcranial direct current stimulation (tDCS) can influence brain network activity and associated cognitive and behavioural functions. In addition to the extensive variety in stimulation parameters, numerous biological factors drive these effects, however these are yet poorly understood. Here, we investigate one of the major biological factors by focusing on sex-dependent effects of tDCS on a challenging cognitive control task (adaptive paced auditory serial addition task [PASAT]) in healthy humans. METHODS This sex-specific re-analysis was performed on data of 163 subjects who underwent a 2-week cognitive control training (6 sessions in total). Subjects received either verum (anodal/cathodal) or sham tDCS. Electrodes were placed over the left or right dorsolateral prefrontal cortex and the respective contralateral deltoid muscle. Cognitive control was measured as performance in the PASAT and was analysed in respect to stimulation conditions (sham, anodal, cathodal) and sex. RESULTS Regardless of stimulation condition, performance gains between the sexes were higher in females compared to males (p = 0.0038). Female's performance during anodal tDCS exceeded male's (p = 0.0070), yet no effects were found for cathodal or sham tDCS. Moreover, in females we found a superior effect for anodal tDCS over sham stimulation (fanodal: p = 0.0354; fcathodal: p = 0.6181), but no such effect in males (manodal: p = 0.6882; mcathodal: p = 0.4822). CONCLUSIONS This study highlights the relevance of biological sex for the effects of tDCS on cognitive training. Thus, an increased attention to biological sex is advisable in future brain stimulation research to highlight and in consequence better understand potentially underlying sex-specific mechanisms. Considering biological sex will further advance customisation and individualisation of tDCS interventions. Trial registration ClinicalTrials.gov, NCT04108663.
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Affiliation(s)
- Simone Weller
- Department of Psychiatry and Psychotherapy, Neurophysiology and Interventional Neuropsychiatry, University of Tübingen, Calwerstraße 14, 72076, Tübingen, Germany
- German Center for Mental Health (DZPG), partner site Tübingen, Germany
| | - Birgit Derntl
- German Center for Mental Health (DZPG), partner site Tübingen, Germany
- Department of Psychiatry and Psychotherapy, Innovative Neuroimaging, University of Tübingen, Calwerstraße 14, 72076, Tübingen, Germany
| | - Christian Plewnia
- Department of Psychiatry and Psychotherapy, Neurophysiology and Interventional Neuropsychiatry, University of Tübingen, Calwerstraße 14, 72076, Tübingen, Germany.
- German Center for Mental Health (DZPG), partner site Tübingen, Germany.
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12
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Andrushko JW, Rinat S, Kirby ED, Dahlby J, Ekstrand C, Boyd LA. Females exhibit smaller volumes of brain activation and lower inter-subject variability during motor tasks. Sci Rep 2023; 13:17698. [PMID: 37848679 PMCID: PMC10582116 DOI: 10.1038/s41598-023-44871-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 10/12/2023] [Indexed: 10/19/2023] Open
Abstract
Past work has shown that brain structure and function differ between females and males. Males have larger cortical and sub-cortical volume and surface area (both total and subregional), while females have greater cortical thickness in most brain regions. Functional differences are also reported in the literature, yet to date little work has systematically considered whether patterns of brain activity indexed with functional magnetic resonance imaging (fMRI) differ between females and males. The current study sought to remediate this issue by employing task-based whole brain motor mapping analyses using an openly available dataset. We tested differences in patterns of functional brain activity associated with 12 voluntary movement patterns in females versus males. Results suggest that females exhibited smaller volumes of brain activation across all 12 movement tasks, and lower patterns of variability in 10 of the 12 movements. We also observed that females had greater cortical thickness, which is in alignment with previous analyses of structural differences. Overall, these findings provide a basis for considering biological sex in future fMRI research and provide a foundation of understanding differences in how neurological pathologies present in females vs males.
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Affiliation(s)
- Justin W Andrushko
- Department of Sport, Exercise and Rehabilitation, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Shie Rinat
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Eric D Kirby
- Faculty of Individualized Interdisciplinary Studies, Simon Fraser University, Burnaby, BC, Canada
| | - Julia Dahlby
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, Canada
| | - Chelsea Ekstrand
- Department of Neuroscience, University of Lethbridge, Lethbridge, AB, Canada.
| | - Lara A Boyd
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, Canada.
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada.
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13
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Bottenhorn KL, Cardenas-Iniguez C, Mills KL, Laird AR, Herting MM. Profiling intra- and inter-individual differences in brain development across early adolescence. Neuroimage 2023; 279:120287. [PMID: 37536527 PMCID: PMC10833064 DOI: 10.1016/j.neuroimage.2023.120287] [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] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 06/27/2023] [Accepted: 07/19/2023] [Indexed: 08/05/2023] Open
Abstract
As we move toward population-level developmental neuroscience, understanding intra- and inter-individual variability in brain maturation and sources of neurodevelopmental heterogeneity becomes paramount. Large-scale, longitudinal neuroimaging studies have uncovered group-level neurodevelopmental trajectories, and while recent work has begun to untangle intra- and inter-individual differences, they remain largely unclear. Here, we aim to quantify both intra- and inter-individual variability across facets of neurodevelopment across early adolescence (ages 8.92 to 13.83 years) in the Adolescent Brain Cognitive Development (ABCD) Study and examine inter-individual variability as a function of age, sex, and puberty. Our results provide novel insight into differences in annualized percent change in macrostructure, microstructure, and functional brain development from ages 9-13 years old. These findings reveal moderate age-related intra-individual change, but age-related differences in inter-individual variability only in a few measures of cortical macro- and microstructure development. Greater inter-individual variability in brain development were seen in mid-pubertal individuals, except for a few aspects of white matter development that were more variable between prepubertal individuals in some tracts. Although both sexes contributed to inter-individual differences in macrostructure and functional development in a few regions of the brain, we found limited support for hypotheses regarding greater male-than-female variability. This work highlights pockets of individual variability across facets of early adolescent brain development, while also highlighting regional differences in heterogeneity to facilitate future investigations in quantifying and probing nuances in normative development, and deviations therefrom.
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Affiliation(s)
- Katherine L Bottenhorn
- Department of Population and Public Health Sciences, University of Southern California, 1845 N Soto St, Los Angeles, CA 90032, USA; Department of Psychology, Florida International University, 11200 SW 8th St, Miami, FL 33199, USA.
| | - Carlos Cardenas-Iniguez
- Department of Population and Public Health Sciences, University of Southern California, 1845 N Soto St, Los Angeles, CA 90032, USA
| | - Kathryn L Mills
- Department of Psychology, University of Oregon, 1227 University St, Eugene, OR 97403, USA
| | - Angela R Laird
- Department of Physics, Florida International University, 11200 SW 8th St, Miami, FL 33199, USA
| | - Megan M Herting
- Department of Population and Public Health Sciences, University of Southern California, 1845 N Soto St, Los Angeles, CA 90032, USA.
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14
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Eliot L, Beery AK, Jacobs EG, LeBlanc HF, Maney DL, McCarthy MM. Why and How to Account for Sex and Gender in Brain and Behavioral Research. J Neurosci 2023; 43:6344-6356. [PMID: 37704386 PMCID: PMC10500996 DOI: 10.1523/jneurosci.0020-23.2023] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 07/14/2023] [Accepted: 07/18/2023] [Indexed: 09/15/2023] Open
Abstract
Long overlooked in neuroscience research, sex and gender are increasingly included as key variables potentially impacting all levels of neurobehavioral analysis. Still, many neuroscientists do not understand the difference between the terms "sex" and "gender," the complexity and nuance of each, or how to best include them as variables in research designs. This TechSights article outlines rationales for considering the influence of sex and gender across taxa, and provides technical guidance for strengthening the rigor and reproducibility of such analyses. This guidance includes the use of appropriate statistical methods for comparing groups as well as controls for key covariates of sex (e.g., total intracranial volume) and gender (e.g., income, caregiver stress, bias). We also recommend approaches for interpreting and communicating sex- and gender-related findings about the brain, which have often been misconstrued by neuroscientists and the lay public alike.
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Affiliation(s)
- Lise Eliot
- Stanson Toshok Center for Brain Function and Repair, Chicago Medical School, Rosalind Franklin University of Medicine & Science, North Chicago, Illinois 60064
| | - Annaliese K Beery
- Department of Integrative Biology, University of California-Berkeley, Berkeley, California 94720
| | - Emily G Jacobs
- Department of Psychological & Brain Sciences, University of California-Santa Barbara, Santa Barbara, California 93106
| | - Hannah F LeBlanc
- Division of the Humanities & Social Sciences, California Institute of Technology, Pasadena, California 91125
| | - Donna L Maney
- Department of Psychology, Emory University, Atlanta, Georgia 30322
| | - Margaret M McCarthy
- Department of Pharmacology, University of Maryland School of Medicine, Baltimore, Maryland 21201
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15
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Guma E, Beauchamp A, Liu S, Levitis E, Ellegood J, Pham L, Mars RB, Raznahan A, Lerch JP. Comparative neuroimaging of sex differences in human and mouse brain anatomy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.23.554334. [PMID: 37662398 PMCID: PMC10473765 DOI: 10.1101/2023.08.23.554334] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
In vivo neuroimaging studies have established several reproducible volumetric sex differences in the human brain, but the causes of such differences are hard to parse. While mouse models are useful for understanding the cellular and mechanistic bases of sex-biased brain development in mammals, there have been no attempts to formally compare mouse and human sex differences across the whole brain to ascertain how well they translate. Addressing this question would shed critical light on use of the mouse as a translational model for sex differences in the human brain and provide insights into the degree to which sex differences in brain volume are conserved across mammals. Here, we use cross-species structural magnetic resonance imaging to carry out the first comparative neuroimaging study of sex-biased neuroanatomical organization of the human and mouse brain. In line with previous findings, we observe that in humans, males have significantly larger and more variable total brain volume; these sex differences are not mirrored in mice. After controlling for total brain volume, we observe modest cross-species congruence in the volumetric effect size of sex across 60 homologous brain regions (r=0.30; e.g.: M>F amygdala, hippocampus, bed nucleus of the stria terminalis, and hypothalamus and F>M anterior cingulate, somatosensory, and primary auditory cortices). This cross-species congruence is greater in the cortex (r=0.33) than non-cortex (r=0.16). By incorporating regional measures of gene expression in both species, we reveal that cortical regions with greater cross-species congruence in volumetric sex differences also show greater cross-species congruence in the expression profile of 2835 homologous genes. This phenomenon differentiates primary sensory regions with high congruence of sex effects and gene expression from limbic cortices where congruence in both these features was weaker between species. These findings help identify aspects of sex-biased brain anatomy present in mice that are retained, lost, or inverted in humans. More broadly, our work provides an empirical basis for targeting mechanistic studies of sex-biased brain development in mice to brain regions that best echo sex-biased brain development in humans.
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Affiliation(s)
- Elisa Guma
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Antoine Beauchamp
- Mouse Imaging Centre, Toronto, Ontario, Canada
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Siyuan Liu
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Elizabeth Levitis
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Jacob Ellegood
- Mouse Imaging Centre, Toronto, Ontario, Canada
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Linh Pham
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Jason P Lerch
- Mouse Imaging Centre, Toronto, Ontario, Canada
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
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16
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Chakrabarty T, Frangou S, Torres IJ, Ge R, Yatham LN. Brain age and cognitive functioning in first-episode bipolar disorder. Psychol Med 2023; 53:5127-5135. [PMID: 35875930 PMCID: PMC10476063 DOI: 10.1017/s0033291722002136] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 06/20/2022] [Accepted: 06/21/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND There is significant heterogeneity in cognitive function in patients with bipolar I disorder (BDI); however, there is a dearth of research into biological mechanisms that might underlie cognitive heterogeneity, especially at disease onset. To this end, this study investigated the association between accelerated or delayed age-related brain structural changes and cognition in early-stage BDI. METHODS First episode patients with BDI (n = 80) underwent cognitive assessment to yield demographically normed composite global and domain-specific scores in verbal memory, non-verbal memory, working memory, processing speed, attention, and executive functioning. Structural magnetic resonance imaging data were also collected from all participants and subjected to machine learning to compute the brain-predicted age difference (brainPAD), calculated by subtracting chronological age from age predicted by neuroimaging data (positive brainPAD values indicating age-related acceleration in brain structural changes and negative values indicating delay). Patients were divided into tertiles based on brainPAD values, and cognitive performance compared amongst tertiles with ANCOVA. RESULTS Patients in the lowest (delayed) tertile of brainPAD values (brainPAD range -17.9 to -6.5 years) had significantly lower global cognitive scores (p = 0.025) compared to patients in the age-congruent tertile (brainPAD range -5.3 to 2.4 yrs), and significantly lower verbal memory scores (p = 0.001) compared to the age-congruent and accelerated (brainPAD range 2.8 to 16.1 yrs) tertiles. CONCLUSION These results provide evidence linking cognitive dysfunction in the early stage of BDI to apparent delay in typical age-related brain changes. Further studies are required to assess how age-related brain changes and cognitive functioning evolve over time.
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Affiliation(s)
- Trisha Chakrabarty
- Department of Psychiatry, University of British Columbia, 2255 Wesbrook Mall, Vancouver, BC, Canada V6T 2A1
| | - Sophia Frangou
- Department of Psychiatry, University of British Columbia, 2255 Wesbrook Mall, Vancouver, BC, Canada V6T 2A1
- Department of Psychiatry Icahn School of Medicine at Mount Sinai, New York City, NY, United States
| | - Ivan J. Torres
- British Columbia Mental Health and Substance Use Services, Vancouver, BC, Canada
| | - Ruiyang Ge
- Department of Psychiatry, University of British Columbia, 2255 Wesbrook Mall, Vancouver, BC, Canada V6T 2A1
| | - Lakshmi N. Yatham
- Department of Psychiatry, University of British Columbia, 2255 Wesbrook Mall, Vancouver, BC, Canada V6T 2A1
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17
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Bukhari H, Su C, Dhamala E, Gu Z, Jamison K, Kuceyeski A. Graph-matching distance between individuals' functional connectomes varies with relatedness, age, and cognitive score. Hum Brain Mapp 2023; 44:3541-3554. [PMID: 37042411 PMCID: PMC10203814 DOI: 10.1002/hbm.26296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 02/10/2023] [Accepted: 03/20/2023] [Indexed: 04/13/2023] Open
Abstract
Functional connectomes (FCs), represented by networks or graphs that summarize coactivation patterns between pairs of brain regions, have been related at a population level to age, sex, cognitive/behavioral scores, life experience, genetics, and disease/disorders. However, quantifying FC differences between individuals also provides a rich source of information with which to map to differences in those individuals' biology, experience, genetics or behavior. In this study, graph matching is used to create a novel inter-individual FC metric, called swap distance, that quantifies the distance between pairs of individuals' partial FCs, with a smaller swap distance indicating the individuals have more similar FC. We apply graph matching to align FCs between individuals from the the Human Connectome ProjectN = 997 and find that swap distance (i) increases with increasing familial distance, (ii) increases with subjects' ages, (iii) is smaller for pairs of females compared to pairs of males, and (iv) is larger for females with lower cognitive scores compared to females with larger cognitive scores. Regions that contributed most to individuals' swap distances were in higher-order networks, that is, default-mode and fronto-parietal, that underlie executive function and memory. These higher-order networks' regions also had swap frequencies that varied monotonically with familial relatedness of the individuals in question. We posit that the proposed graph matching technique provides a novel way to study inter-subject differences in FC and enables quantification of how FC may vary with age, relatedness, sex, and behavior.
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Affiliation(s)
- Hussain Bukhari
- Department of NeuroscienceWeill Cornell MedicineNew YorkNew YorkUSA
| | - Chang Su
- Department of BiostatisticsYale UniversityNew HavenConnecticutUSA
| | - Elvisha Dhamala
- Department of PsychologyYale UniversityNew HavenConnecticutUSA
| | - Zijin Gu
- Department of Electrical and Computer EngineeringCornell UniversityIthacaNew YorkUSA
| | - Keith Jamison
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
| | - Amy Kuceyeski
- Department of RadiologyWeill Cornell MedicineNew YorkNew YorkUSA
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18
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Cocquyt EM, Depuydt E, Santens P, van Mierlo P, Duyck W, Szmalec A, De Letter M. Effects of Healthy Aging and Gender on the Electrophysiological Correlates of Semantic Sentence Comprehension: The Development of Dutch Normative Data. JOURNAL OF SPEECH, LANGUAGE, AND HEARING RESEARCH : JSLHR 2023; 66:1694-1717. [PMID: 37093923 DOI: 10.1044/2023_jslhr-22-00545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
PURPOSE The clinical use of event-related potentials in patients with language disorders is increasingly acknowledged. For this purpose, normative data should be available. Within this context, healthy aging and gender effects on the electrophysiological correlates of semantic sentence comprehension were investigated. METHOD One hundred and ten healthy subjects (55 men and 55 women), divided among three age groups (young, middle aged, and elderly), performed a semantic sentence congruity task in the visual modality during electroencephalographic recording. RESULTS The early visual complex was affected by increasing age as shown by smaller P2 amplitudes in the elderly compared to the young. Moreover, the N400 effect in the elderly was smaller than in the young and was delayed compared to latency measures in both middle-aged and young subjects. The topography of age-related amplitude changes of the N400 effect appeared to be gender specific. The late positive complex effect was increased at frontal electrode sites from middle age on, but this was not statistically significant. No gender effects were detected regarding the early P1, N1, and P2, or the late positive complex effect. CONCLUSION Especially aging effects were found during semantic sentence comprehension, and this from the level of perceptual processing on. Normative data are now available for clinical use.
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Affiliation(s)
| | - Emma Depuydt
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Belgium
| | | | - Pieter van Mierlo
- Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Belgium
| | - Wouter Duyck
- Department of Experimental Psychology, Faculty of Psychology and Educational Sciences, Ghent University, Belgium
| | - Arnaud Szmalec
- Department of Experimental Psychology, Faculty of Psychology and Educational Sciences, Ghent University, Belgium
- Psychological Sciences Research Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Miet De Letter
- Department of Rehabilitation Sciences, Ghent University, Belgium
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19
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Strike LT, Hansell NK, Chuang KH, Miller JL, de Zubicaray GI, Thompson PM, McMahon KL, Wright MJ. The Queensland Twin Adolescent Brain Project, a longitudinal study of adolescent brain development. Sci Data 2023; 10:195. [PMID: 37031232 PMCID: PMC10082846 DOI: 10.1038/s41597-023-02038-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 02/22/2023] [Indexed: 04/10/2023] Open
Abstract
We describe the Queensland Twin Adolescent Brain (QTAB) dataset and provide a detailed methodology and technical validation to facilitate data usage. The QTAB dataset comprises multimodal neuroimaging, as well as cognitive and mental health data collected in adolescent twins over two sessions (session 1: N = 422, age 9-14 years; session 2: N = 304, 10-16 years). The MRI protocol consisted of T1-weighted (MP2RAGE), T2-weighted, FLAIR, high-resolution TSE, SWI, resting-state fMRI, DWI, and ASL scans. Two fMRI tasks were added in session 2: an emotional conflict task and a passive movie-watching task. Outside of the scanner, we assessed cognitive function using standardised tests. We also obtained self-reports of symptoms for anxiety and depression, perceived stress, sleepiness, pubertal development measures, and risk and protective factors. We additionally collected several biological samples for genomic and metagenomic analysis. The QTAB project was established to promote health-related research in adolescence.
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Affiliation(s)
- Lachlan T Strike
- The University of Queensland, Queensland Brain Institute, Brisbane, QLD 4072, Australia.
- School of Psychology and Counselling, Faculty of Health, Queensland University of Technology, Kelvin Grove, QLD 4059, Australia.
- Psychiatric Genetics, QIMR Berghofer Medical Research Institute, QLD, 4006, Brisbane, Australia.
| | - Narelle K Hansell
- The University of Queensland, Queensland Brain Institute, Brisbane, QLD 4072, Australia
| | - Kai-Hsiang Chuang
- The University of Queensland, Queensland Brain Institute, Brisbane, QLD 4072, Australia
- The University of Queensland, Centre for Advanced Imaging, Brisbane, QLD 4072, Australia
| | - Jessica L Miller
- The University of Queensland, Queensland Brain Institute, Brisbane, QLD 4072, Australia
| | - Greig I de Zubicaray
- School of Psychology and Counselling, Faculty of Health, Queensland University of Technology, Kelvin Grove, QLD 4059, Australia
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, USA
| | - Katie L McMahon
- School of Clinical Sciences, Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Margaret J Wright
- The University of Queensland, Queensland Brain Institute, Brisbane, QLD 4072, Australia
- The University of Queensland, Centre for Advanced Imaging, Brisbane, QLD 4072, Australia
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20
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Navarri X, Vosberg DE, Shin J, Richer L, Leonard G, Pike GB, Banaschewski T, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Martinot MLP, Artiges E, Nees F, Orfanos DP, Poustka L, Hohmann S, Fröhner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Schumann G, Pausova Z, Paus T. A biologically informed polygenic score of neuronal plasticity moderates the association between cognitive aptitudes and cortical thickness in adolescents. Dev Cogn Neurosci 2023; 60:101232. [PMID: 36963244 PMCID: PMC10064237 DOI: 10.1016/j.dcn.2023.101232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 03/14/2023] [Accepted: 03/15/2023] [Indexed: 03/17/2023] Open
Abstract
Although many studies of the adolescent brain identified positive associations between cognitive abilities and cortical thickness, little is known about mechanisms underlying such brain-behavior relationships. With experience-induced plasticity playing an important role in shaping the cerebral cortex throughout life, it is likely that some of the inter-individual variations in cortical thickness could be explained by genetic variations in relevant molecular processes, as indexed by a polygenic score of neuronal plasticity (PGS-NP). Here, we studied associations between PGS-NP, cognitive abilities, and thickness of the cerebral cortex, estimated from magnetic resonance images, in the Saguenay Youth Study (SYS, 533 females, 496 males: age=15.0 ± 1.8 years of age; cross-sectional), and the IMAGEN Study (566 females, 556 males; between 14 and 19 years; longitudinal). Using Gene Ontology, we first identified 199 genes implicated in neuronal plasticity, which mapped to 155,600 single nucleotide polymorphisms (SNPs). Second, we estimated their effect sizes from an educational attainment meta-GWAS to build a PGS-NP. Third, we examined a possible moderating role of PGS-NP in the relationship between performance intelligence quotient (PIQ), and its subtests, and the thickness of 34 cortical regions. In SYS, we observed a significant interaction between PGS-NP and object assembly vis-à-vis thickness in male adolescents (p = 0.026). A median-split analysis showed that, in males with a 'high' PGS-NP, stronger associations between object assembly and thickness were found in regions with larger age-related changes in thickness (r = 0.55, p = 0.00075). Although the interaction between PIQ and PGS-NP was non-significant (p = 0.064), we performed a similar median-split analysis. Again, in the high PGS-NP males, positive associations between PIQ and thickness were observed in regions with larger age-related changes in thickness (r = 0.40, p = 0.018). In the IMAGEN cohort, we did not replicate the first set of results (interaction between PGS-NP and cognitive abilities via-a-vis cortical thickness) while we did observe the same relationship between the brain-behaviour relationship and (longitudinal) changes in cortical thickness (Matrix reasoning: r = 0.63, p = 6.5e-05). No statistically significant results were observed in female adolescents in either cohort. Overall, these cross-sectional and longitudinal results suggest that molecular mechanisms involved in neuronal plasticity may contribute to inter-individual variations of cortical thickness related to cognitive abilities during adolescence in a sex-specific manner.
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Affiliation(s)
- Xavier Navarri
- Departments of Psychiatry and Neuroscience, Université de Montreal, Montreal, QC H3T 1J4, Canada; CHU Sainte-Justine Research Centre, Montreal, QC H3T 1C5, Canada
| | - Daniel E Vosberg
- Departments of Psychiatry and Neuroscience, Université de Montreal, Montreal, QC H3T 1J4, Canada; CHU Sainte-Justine Research Centre, Montreal, QC H3T 1C5, Canada
| | - Jean Shin
- Hospital for Sick Children, University of Toronto, Toronto, ON M5G 1X8, Canada
| | - Louis Richer
- Department of Health Sciences, Université du Québec à Chicoutimi, Chicoutimi, QC G7H 2B1, Canada
| | - Gabriel Leonard
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - G Bruce Pike
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 4N1, Canada
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, United Kingdom
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany; Department of Psychology, School of Social Sciences, University of Mannheim, 68131 Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, 05405 Burlington, VT, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie"; Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales & psychiatrie", University Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS; Centre Borelli, Gif-sur-Yvette, France; and AP-HP. Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie"; Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette; and Psychiatry Department, EPS Barthélémy Durand, Etampes, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany; Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | | | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075 Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Germany; Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Zdenka Pausova
- Departments of Physiology and Nutritional Sciences, Hospital for Sick Children, University of Toronto, Peter Gilgan Centre for Research and Learning, Toronto, ON M5G 0A4, Canada
| | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Université de Montreal, Montreal, QC H3T 1J4, Canada; CHU Sainte-Justine Research Centre, Montreal, QC H3T 1C5, Canada; Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON M5S3G3, Canada.
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21
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Voskuhl R, Itoh Y. The X factor in neurodegeneration. J Exp Med 2022; 219:e20211488. [PMID: 36331399 PMCID: PMC9641640 DOI: 10.1084/jem.20211488] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 06/22/2022] [Accepted: 10/12/2022] [Indexed: 07/25/2023] Open
Abstract
Given the aging population, it is important to better understand neurodegeneration in aging healthy people and to address the increasing incidence of neurodegenerative diseases. It is imperative to apply novel strategies to identify neuroprotective therapeutics. The study of sex differences in neurodegeneration can reveal new candidate treatment targets tailored for women and men. Sex chromosome effects on neurodegeneration remain understudied and represent a promising frontier for discovery. Here, we will review sex differences in neurodegeneration, focusing on the study of sex chromosome effects in the context of declining levels of sex hormones during aging.
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Affiliation(s)
- Rhonda Voskuhl
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA
| | - Yuichiro Itoh
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA
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22
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Hayashi W, Hanawa Y, Saga N, Nakamura D, Iwanami A. ASD symptoms in adults with ADHD: a comparative study using ADOS-2. Eur Arch Psychiatry Clin Neurosci 2022; 272:1481-1494. [PMID: 34993599 DOI: 10.1007/s00406-021-01362-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Accepted: 11/24/2021] [Indexed: 11/26/2022]
Abstract
In this study, we examined autism spectrum disorder (ASD) symptoms in adults with attention-deficit hyperactivity disorder (ADHD) in comparison with normal controls using the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2). Sixty-three adults with ADHD (mean age, 35.3 years; 38 men) and 31 controls (mean age, 38.7 years; 17 men) completed Module 4 of the ADOS-2, Autism Spectrum Quotient, Conners' Adult ADHD Rating Scale, and Wechsler Adult Intelligence Scale, Third Edition. Adults with ADHD were not clinically diagnosed with ASD, and their ADHD diagnosis was based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Between-group comparisons on the scoring patterns revealed significant ASD symptoms present in adults with ADHD, which was congruent with our previous study. Further, item level and correlation analyses showed the possibility that ASD symptoms in adult ADHD comprised of two distinct mechanisms, one qualitatively similar to ASD and the other arising from ADHD characteristics, highlighting the complex nature of ADHD-ASD symptom overlaps.
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Affiliation(s)
- Wakaho Hayashi
- Department of Psychiatry, Showa University School of Medicine, 6-11-11 Kitakarasuyama, Setagaya-ku, Tokyo, 157-8577, Japan.
| | - Yoichi Hanawa
- Department of Psychiatry, Showa University School of Medicine, 6-11-11 Kitakarasuyama, Setagaya-ku, Tokyo, 157-8577, Japan
| | - Nobuyuki Saga
- Department of Psychiatry, Showa University School of Medicine, 6-11-11 Kitakarasuyama, Setagaya-ku, Tokyo, 157-8577, Japan
| | - Dan Nakamura
- Department of Psychiatry, Showa University School of Medicine, 6-11-11 Kitakarasuyama, Setagaya-ku, Tokyo, 157-8577, Japan
| | - Akira Iwanami
- Department of Psychiatry, Showa University School of Medicine, 6-11-11 Kitakarasuyama, Setagaya-ku, Tokyo, 157-8577, Japan
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23
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Modabbernia A, Whalley HC, Glahn DC, Thompson PM, Kahn RS, Frangou S. Systematic evaluation of machine learning algorithms for neuroanatomically-based age prediction in youth. Hum Brain Mapp 2022; 43:5126-5140. [PMID: 35852028 PMCID: PMC9812239 DOI: 10.1002/hbm.26010] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 05/25/2022] [Accepted: 06/27/2022] [Indexed: 01/15/2023] Open
Abstract
Application of machine learning (ML) algorithms to structural magnetic resonance imaging (sMRI) data has yielded behaviorally meaningful estimates of the biological age of the brain (brain-age). The choice of the ML approach in estimating brain-age in youth is important because age-related brain changes in this age-group are dynamic. However, the comparative performance of the available ML algorithms has not been systematically appraised. To address this gap, the present study evaluated the accuracy (mean absolute error [MAE]) and computational efficiency of 21 machine learning algorithms using sMRI data from 2105 typically developing individuals aged 5-22 years from five cohorts. The trained models were then tested in two independent holdout datasets, one comprising 4078 individuals aged 9-10 years and another comprising 594 individuals aged 5-21 years. The algorithms encompassed parametric and nonparametric, Bayesian, linear and nonlinear, tree-based, and kernel-based models. Sensitivity analyses were performed for parcellation scheme, number of neuroimaging input features, number of cross-validation folds, number of extreme outliers, and sample size. Tree-based models and algorithms with a nonlinear kernel performed comparably well, with the latter being especially computationally efficient. Extreme Gradient Boosting (MAE of 1.49 years), Random Forest Regression (MAE of 1.58 years), and Support Vector Regression (SVR) with Radial Basis Function (RBF) Kernel (MAE of 1.64 years) emerged as the three most accurate models. Linear algorithms, with the exception of Elastic Net Regression, performed poorly. Findings of the present study could be used as a guide for optimizing methodology when quantifying brain-age in youth.
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Affiliation(s)
| | - Heather C. Whalley
- Division of PsychiatryUniversity of Edinburgh, Kennedy Tower, Royal Edinburgh HospitalEdinburghUK
| | - David C. Glahn
- Boston Children's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Rene S. Kahn
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Sophia Frangou
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain HealthUniversity of British ColumbiaVancouverBritish ColumbiaCanada
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24
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Brain network architecture constrains age-related cortical thinning. Neuroimage 2022; 264:119721. [PMID: 36341953 DOI: 10.1016/j.neuroimage.2022.119721] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 10/23/2022] [Accepted: 10/28/2022] [Indexed: 11/06/2022] Open
Abstract
Age-related cortical atrophy, approximated by cortical thickness measurements from magnetic resonance imaging, follows a characteristic pattern over the lifespan. Although its determinants remain unknown, mounting evidence demonstrates correspondence between the connectivity profiles of structural and functional brain networks and cortical atrophy in health and neurological disease. Here, we performed a cross-sectional multimodal neuroimaging analysis of 2633 individuals from a large population-based cohort to characterize the association between age-related differences in cortical thickness and functional as well as structural brain network topology. We identified a widespread pattern of age-related cortical thickness differences including "hotspots" of pronounced age effects in sensorimotor areas. Regional age-related differences were strongly correlated within the structurally defined node neighborhood. The overall pattern of thickness differences was found to be anchored in the functional network hierarchy as encoded by macroscale functional connectivity gradients. Lastly, the identified difference pattern covaried significantly with cognitive and motor performance. Our findings indicate that connectivity profiles of functional and structural brain networks act as organizing principles behind age-related cortical thinning as an imaging surrogate of cortical atrophy.
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25
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Alexopoulos J, Giordano V, Doering S, Seidl R, Benavides-Varela S, Russwurm M, Greenwood S, Berger A, Bartha-Doering L. Sex differences in neural processing of speech in neonates. Cortex 2022; 157:117-128. [PMID: 36279755 DOI: 10.1016/j.cortex.2022.09.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 05/24/2022] [Accepted: 09/04/2022] [Indexed: 12/15/2022]
Abstract
The large majority of studies shows that girls develop their language skills faster than boys in the first few years of life. Are girls born with this advantage in language development? The present study used fNIRS in neonates to investigate sex differences in neural processing of speech within the first days of life. We found that speech stimuli elicited significantly more brain activity than non-speech stimuli in both groups of male and female neonates. However, whereas girls showed significant HbO changes to speech stimuli only within the left hemisphere, boys exhibited simultaneous neural activations in both hemispheres, with a larger and more significant fronto-temporal cluster in the right hemisphere. Furthermore, in boys, the variation in time-to-peak latencies was considerably greater than in girls. These findings suggest an earlier maturation of language-related brain areas in girls and highlight the importance of sex-specific investigations of neural language networks in infants.
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Affiliation(s)
- Johanna Alexopoulos
- Department of Psychoanalysis and Psychotherapy, Medical University of Vienna, Vienna, Austria; Department of Pediatrics and Adolescent Medicine, Comprehensive Center for Pediatrics, Medical University of Vienna, Vienna, Austria
| | - Vito Giordano
- Department of Pediatrics and Adolescent Medicine, Comprehensive Center for Pediatrics, Medical University of Vienna, Vienna, Austria
| | - Stephan Doering
- Department of Psychoanalysis and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Rainer Seidl
- Department of Pediatrics and Adolescent Medicine, Comprehensive Center for Pediatrics, Medical University of Vienna, Vienna, Austria
| | - Silvia Benavides-Varela
- Department of Developmental Psychology and Socialization & Department of Neuroscience, University of Padova, Padova, Italy
| | - Magdalena Russwurm
- Department of Pediatrics and Adolescent Medicine, Comprehensive Center for Pediatrics, Medical University of Vienna, Vienna, Austria
| | - Stephanie Greenwood
- Department of Pediatrics and Adolescent Medicine, Comprehensive Center for Pediatrics, Medical University of Vienna, Vienna, Austria
| | - Angelika Berger
- Department of Pediatrics and Adolescent Medicine, Comprehensive Center for Pediatrics, Medical University of Vienna, Vienna, Austria
| | - Lisa Bartha-Doering
- Department of Pediatrics and Adolescent Medicine, Comprehensive Center for Pediatrics, Medical University of Vienna, Vienna, Austria.
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26
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Colby AE, DeCasien AR, Cooper EB, Higham JP. Greater variability in rhesus macaque ( Macaca mulatta) endocranial volume among males than females. Proc Biol Sci 2022; 289:20220728. [PMID: 36350207 PMCID: PMC9653222 DOI: 10.1098/rspb.2022.0728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 10/05/2022] [Indexed: 11/11/2023] Open
Abstract
The greater male variability (GMV) hypothesis proposes that traits are more variable among males than females, and is supported by numerous empirical studies. Interestingly, GMV is also observed for human brain size and internal brain structure, a pattern which may have implications for sex-biased neurological and psychiatric conditions. A better understanding of neuroanatomical variability in non-human primates may illuminate whether certain species are appropriate models for these conditions. Here, we tested for sex differences in the variability of endocranial volume (ECV, a proxy for brain size) in a sample of 542 rhesus macaques (Macaca mulatta) from a large pedigreed free-ranging population. We also examined the components of phenotypic variance (additive genetic and residual variance) to tease apart the potential drivers of sex differences in variability. Our results suggest that males exhibit more variable ECVs, and that this pattern reflects either balancing/disruptive selection on male behaviour (associated with alternative male mating strategies) or sex chromosome effects (associated with mosaic patterns of X chromosome gene expression in females), rather than extended neurodevelopment among males. This represents evidence of GMV for brain size in a non-human primate species and highlights the potential of rhesus macaques as a model for sex-biased brain-based disorders.
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Affiliation(s)
- Abigail E. Colby
- Department of Anthropology, New York University, New York, NY, USA
- Department of Anthropology and Archaeology, University of Calgary, Calgary, AB, Canada
| | - Alex R. DeCasien
- Department of Anthropology, New York University, New York, NY, USA
- New York Consortium in Evolutionary Primatology, New York, NY, USA
- Section on Developmental Neurogenomics, National Institutes of Health, Bethesda, MD, USA
| | - Eve B. Cooper
- Department of Anthropology, New York University, New York, NY, USA
- New York Consortium in Evolutionary Primatology, New York, NY, USA
| | - James P. Higham
- Department of Anthropology, New York University, New York, NY, USA
- New York Consortium in Evolutionary Primatology, New York, NY, USA
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27
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Freeman HB, Lee J. Sex Differences in Cognition in Schizophrenia: What We Know and What We Do Not Know. Curr Top Behav Neurosci 2022; 63:463-474. [PMID: 36271194 DOI: 10.1007/7854_2022_394] [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] [Indexed: 02/20/2023]
Abstract
Cognitive impairment is a core feature of schizophrenia. This selective review examines whether schizophrenia patients show preserved sexual dimorphism in cognition. Existing studies using performance tasks largely show comparable sex effects between schizophrenia patients and healthy populations. This pattern appears to be similar across multiple cognitive domains and across phase of illness. Our selective review also identifies several unresolved questions about sex differences in cognition in schizophrenia. A better understanding of sex differences in cognition in schizophrenia may provide important clues to probing the relationship between cognitive impairment and pathophysiological processes of the disorder.
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Affiliation(s)
- Hyun Bin Freeman
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Junghee Lee
- Department of Psychiatry and Behavioral Neurobiology, The University of Alabama at Birmingham, Birmingham, AL, USA.
- Comprehensive Neuroscience Center, The University of Alabama at Birmingham, Birmingham, AL, USA.
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28
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Hennessy A, Seguin D, Correa S, Wang J, Martinez-Trujillo JC, Nicolson R, Duerden EG. Anxiety in children and youth with autism spectrum disorder and the association with amygdala subnuclei structure. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2022; 27:1053-1067. [PMID: 36278283 PMCID: PMC10108338 DOI: 10.1177/13623613221127512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Autism spectrum disorder (ASD) is clinically characterized by social and communication difficulties as well as repetitive behaviors. Many children with ASD also suffer from anxiety, which has been associated with alterations in amygdala structure. In this work, the association between amygdala subnuclei volumes and anxiety was assessed in a cohort of 234 participants (mean age = 11.0 years, SD = 3.9, 95 children with ASD, 139 children were non-autistic). Children underwent magnetic resonance imaging. Amygdala subnuclei volumes were extracted automatically. Anxiety was assessed using the Screen for Child Anxiety Related Disorders, the Child Behavior Checklist, and the Strength and Difficulties Questionnaire. Children with ASD had higher anxiety scores relative to non-autistic children on all anxiety measures (all, p < 0.05). Anxiety levels were significantly predicted in children with ASD by right basal (right: B = 0.235, p = 0.002) and paralaminar (PL) (B = −0.99, p = 0.009) volumes. Basal nuclei receive multisensory information from cortical and subcortical areas and have extensive projections within the limbic system while the PL nuclei are involved in emotional processing. Alterations in basal and PL nuclei in children with ASD and the association with anxiety may reflect morphological changes related to in the neurocircuitry of anxiety in ASD. Lay abstract Autism spectrum disorder (ASD) is clinically characterized by social communication difficulties as well as restricted and repetitive patterns of behavior. In addition, children with ASD are more likely to experience anxiety compared with their peers who do not have ASD. Recent studies suggest that atypical amygdala structure, a brain region involved in emotions, may be related to anxiety in children with ASD. However, the amygdala is a complex structure composed of heterogeneous subnuclei, and few studies to date have focused on how amygdala subnuclei relate to in anxiety in this population. The current sample consisted of 95 children with ASD and 139 non-autistic children, who underwent magnetic resonance imaging (MRI) and assessments for anxiety. The amygdala volumes were automatically segmented. Results indicated that children with ASD had elevated anxiety scores relative to peers without ASD. Larger basal volumes predicted greater anxiety in children with ASD, and this association was not seen in non-autistic children. Findings converge with previous literature suggesting ASD children suffer from higher levels of anxiety than non-autistic children, which may have important implications in treatment and interventions. Our results suggest that volumetric estimation of amygdala’s subregions in MRI may reveal specific anxiety-related associations in children with ASD.
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Affiliation(s)
| | | | | | | | | | | | - Emma G Duerden
- Western University, Canada
- The University of Western Ontario, Canada
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29
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Sanford N, Ge R, Antoniades M, Modabbernia A, Haas SS, Whalley HC, Galea L, Popescu SG, Cole JH, Frangou S. Sex differences in predictors and regional patterns of brain age gap estimates. Hum Brain Mapp 2022; 43:4689-4698. [PMID: 35790053 PMCID: PMC9491279 DOI: 10.1002/hbm.25983] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 06/01/2022] [Accepted: 06/01/2022] [Indexed: 11/11/2022] Open
Abstract
The brain-age-gap estimate (brainAGE) quantifies the difference between chronological age and age predicted by applying machine-learning models to neuroimaging data and is considered a biomarker of brain health. Understanding sex differences in brainAGE is a significant step toward precision medicine. Global and local brainAGE (G-brainAGE and L-brainAGE, respectively) were computed by applying machine learning algorithms to brain structural magnetic resonance imaging data from 1113 healthy young adults (54.45% females; age range: 22-37 years) participating in the Human Connectome Project. Sex differences were determined in G-brainAGE and L-brainAGE. Random forest regression was used to determine sex-specific associations between G-brainAGE and non-imaging measures pertaining to sociodemographic characteristics and mental, physical, and cognitive functions. L-brainAGE showed sex-specific differences; in females, compared to males, L-brainAGE was higher in the cerebellum and brainstem and lower in the prefrontal cortex and insula. Although sex differences in G-brainAGE were minimal, associations between G-brainAGE and non-imaging measures differed between sexes with the exception of poor sleep quality, which was common to both. While univariate relationships were small, the most important predictor of higher G-brainAGE was self-identification as non-white in males and systolic blood pressure in females. The results demonstrate the value of applying sex-specific analyses and machine learning methods to advance our understanding of sex-related differences in factors that influence the rate of brain aging and provide a foundation for targeted interventions.
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Affiliation(s)
- Nicole Sanford
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Ruiyang Ge
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Mathilde Antoniades
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | - Liisa Galea
- Department of Psychology, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - James H Cole
- Centre for Medical Image Computing, University College London, London, UK
- Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK
| | - Sophia Frangou
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Sanders AFP, Baum GL, Harms MP, Kandala S, Bookheimer SY, Dapretto M, Somerville LH, Thomas KM, Van Essen DC, Yacoub E, Barch DM. Developmental trajectories of cortical thickness by functional brain network: The roles of pubertal timing and socioeconomic status. Dev Cogn Neurosci 2022; 57:101145. [PMID: 35944340 PMCID: PMC9386024 DOI: 10.1016/j.dcn.2022.101145] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 07/20/2022] [Accepted: 08/04/2022] [Indexed: 11/20/2022] Open
Abstract
The human cerebral cortex undergoes considerable changes during development, with cortical maturation patterns reflecting regional heterogeneity that generally progresses in a posterior-to-anterior fashion. However, the organizing principles that govern cortical development remain unclear. In the current study, we characterized age-related differences in cortical thickness (CT) as a function of sex, pubertal timing, and two dissociable indices of socioeconomic status (i.e., income-to-needs and maternal education) in the context of functional brain network organization, using a cross-sectional sample (n = 789) diverse in race, ethnicity, and socioeconomic status from the Lifespan Human Connectome Project in Development (HCP-D). We found that CT generally followed a linear decline from 5 to 21 years of age, except for three functional networks that displayed nonlinear trajectories. We found no main effect of sex or age by sex interaction for any network. Earlier pubertal timing was associated with reduced mean CT and CT in seven networks. We also found a significant age by maternal education interaction for mean CT across cortex and CT in the dorsal attention network, where higher levels of maternal education were associated with steeper age-related decreases in CT. Taken together, our results suggest that these biological and environmental variations may impact the emerging functional connectome.
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Affiliation(s)
- Ashley F P Sanders
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA.
| | - Graham L Baum
- Department of Psychology, Harvard University, Cambridge, MA 02138, USA
| | - Michael P Harms
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Sridhar Kandala
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Susan Y Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles School of Medicine, Los Angeles, CA 90095, USA
| | - Mirella Dapretto
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles School of Medicine, Los Angeles, CA 90095, USA
| | - Leah H Somerville
- Department of Psychology, Harvard University, Cambridge, MA 02138, USA
| | - Kathleen M Thomas
- Institute of Child Development, University of Minnesota, Minneapolis, MN 55455, USA
| | - David C Van Essen
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN 55455, USA
| | - Deanna M Barch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
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31
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Summers V. Sex differences in number of X chromosomes and X-chromosome inactivation in females promote greater variability in hearing among males. Biol Sex Differ 2022; 13:49. [PMID: 36114557 PMCID: PMC9482204 DOI: 10.1186/s13293-022-00457-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 08/27/2022] [Indexed: 01/19/2023] Open
Abstract
Background For more than 150 years, research studies have documented greater variability across males than across females (“greater male variability”—GMV) over a broad range of behavioral and morphological measures. In placental mammals, an ancient difference between males and females that may make an important contribution to GMV is the different pattern of activation of X chromosomes across cells in females (mosaic inactivation of one the two X chromosomes across cells) vs males (consistent activation of a single X chromosome in all cells). In the current study, variability in hearing thresholds was examined for human listeners with thresholds within the normal range. Initial analyses compared variability in thresholds across males vs. across females. If greater across-male than across-female variability was present, and if these differences in variability related to the different patterns X-chromosome activation in males vs. females, it was expected that correlations between related measures within a given subject (e.g., hearing thresholds at given frequency in the two ears) would be greater in males than females. Methods Hearing thresholds at audiometric test frequencies (500–6000 or 500–8000 Hz) were extracted from two datasets representing more than 8500 listeners with normal hearing (4590 males, 4376 females). Separate data analyses were carried out on each dataset to compare: (1) relative variability in hearing thresholds across males vs. across females at each test frequency; (2) correlations between both across-ear and within-ear hearing thresholds within males vs. within females, and (3) mean thresholds for females vs. males at each frequency. Results A consistent pattern of GMV in hearing thresholds was seen across frequencies in both datasets. In addition, both across-ear and within-ear correlations between thresholds were consistently greater in males than females. Previous studies have frequently reported lower mean thresholds for females than males for listeners with normal hearing. One of the datasets replicated this result, showing a clear and consistent pattern of lower mean thresholds for females. The second data set did not show clear evidence of this female advantage. Conclusions Hearing thresholds showed clear evidence of greater variability across males than across females and higher correlations across related threshold measures within males than within females. The results support a link between the observed GMV and the mosaic pattern of X-activation for females that is not present in males. Supplementary Information The online version contains supplementary material available at 10.1186/s13293-022-00457-9. Greater variability in hearing thresholds across males than females for human listeners with thresholds within the normal range. Higher within-ear and between-ear correlations between thresholds for males than females consistent with sex chromosome effects on variability NIH-mandated inclusion of sex as a biological variable should include sex differences in variability and underlying mechanisms
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Sex differences in the human brain: a roadmap for more careful analysis and interpretation of a biological reality. Biol Sex Differ 2022; 13:43. [PMID: 35883159 PMCID: PMC9327177 DOI: 10.1186/s13293-022-00448-w] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 05/23/2022] [Indexed: 12/15/2022] Open
Abstract
The presence, magnitude, and significance of sex differences in the human brain are hotly debated topics in the scientific community and popular media. This debate is largely fueled by studies containing strong, opposing conclusions: either little to no evidence exists for sex differences in human neuroanatomy, or there are small-to-moderate differences in the size of certain brain regions that are highly reproducible across cohorts (even after controlling for sex differences in average brain size). Our Commentary uses the specific comparison between two recent large-scale studies that adopt these opposing views-namely the review by Eliot and colleagues (2021) and the direct analysis of ~ 40k brains by Williams and colleagues (2021)-in an effort to clarify this controversy and provide a framework for conducting this research. First, we review observations that motivate research on sex differences in human neuroanatomy, including potential causes (evolutionary, genetic, and environmental) and effects (epidemiological and clinical evidence for sex-biased brain disorders). We also summarize methodological and empirical support for using structural MRI to investigate such patterns. Next, we outline how researchers focused on sex differences can better specify their study design (e.g., how sex was defined, if and how brain size was adjusted for) and results (by e.g., distinguishing sexual dimorphisms from sex differences). We then compare the different approaches available for studying sex differences across a large number of individuals: direct analysis, meta-analysis, and review. We stress that reviews do not account for methodological differences across studies, and that this variation explains many of the apparent inconsistencies reported throughout recent reviews (including the work by Eliot and colleagues). For instance, we show that amygdala volume is consistently reported as male-biased in studies with sufficient sample sizes and appropriate methods for brain size correction. In fact, comparing the results from multiple large direct analyses highlights small, highly reproducible sex differences in the volume of many brain regions (controlling for brain size). Finally, we describe best practices for the presentation and interpretation of these findings. Care in interpretation is important for all domains of science, but especially so for research on sex differences in the human brain, given the existence of broad societal gender-biases and a history of biological data being used justify sexist ideas. As such, we urge researchers to discuss their results from simultaneously scientific and anti-sexist viewpoints.
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Reply to Ayuso García et al. Health Perception among Female COVID-19 Patients. Comment on “Fernández-de-las-Peñas et al. Female Sex Is a Risk Factor Associated with Long-Term Post-COVID Related-Symptoms but Not with COVID-19 Symptoms: The LONG-COVID-EXP-CM Multicenter Study. J. Clin. Med. 2022, 11, 413”. J Clin Med 2022; 11:jcm11133616. [PMID: 35806901 PMCID: PMC9267921 DOI: 10.3390/jcm11133616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 05/25/2022] [Accepted: 06/20/2022] [Indexed: 11/30/2022] Open
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Zhao L, Matloff W, Shi Y, Cabeen RP, Toga AW. Mapping Complex Brain Torque Components and Their Genetic Architecture and Phenomic Associations in 24,112 Individuals. Biol Psychiatry 2022; 91:753-768. [PMID: 35027165 PMCID: PMC8957509 DOI: 10.1016/j.biopsych.2021.11.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 10/29/2021] [Accepted: 11/01/2021] [Indexed: 12/19/2022]
Abstract
BACKGROUND The functional significance and mechanisms determining the development and individual variability of structural brain asymmetry remain unclear. Here, we systematically analyzed all relevant components of the most prominent structural asymmetry, brain torque (BT), and their relationships with potential genetic and nongenetic modifiers in a sample comprising 24,112 individuals from six cohorts. METHODS BT features, including petalia, bending, dorsoventral shift, brain tissue distribution asymmetries, and cortical surface positional asymmetries, were directly modeled using a set of automatic three-dimensional brain shape analysis approaches. Age-, sex-, and handedness-related effects on BT were assessed. The genetic architecture and phenomic associations of BT were investigated using genome- and phenome-wide association scans. RESULTS Our results confirmed the population-level predominance of the typical counterclockwise torque and suggested a first attenuating, then enlarging dynamic across the life span (3-81 years) primarily for frontal, occipital, and perisylvian BT features. Sex/handedness, BT, and cognitive function of verbal-numerical reasoning were found to be interrelated statistically. We observed differential heritability of up to 56% for BT, especially in temporal language areas. Individual variations of BT were also associated with various phenotypic variables of neuroanatomy, cognition, lifestyle, sociodemographics, anthropometry, physical health, and adult and child mental health. Our genomic analyses identified a number of genetic associations at lenient significance levels, which need to be further validated using larger samples in the future. CONCLUSIONS This study provides a comprehensive description of BT and insights into biological and other factors that may contribute to the development and individual variations of BT.
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Affiliation(s)
- Lu Zhao
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, California
| | - William Matloff
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, California
| | - Yonggang Shi
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, California
| | - Ryan P Cabeen
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, California
| | - Arthur W Toga
- Laboratory of Neuro Imaging, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, California.
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Investigation of motor self-monitoring deficits in schizophrenia with passivity experiences using a novel modified joint position matching paradigm. Eur Arch Psychiatry Clin Neurosci 2022; 272:509-518. [PMID: 33837844 DOI: 10.1007/s00406-021-01261-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Accepted: 03/30/2021] [Indexed: 10/21/2022]
Abstract
Numerous studies have identified deficits in the self-monitoring system that are associated with schizophrenia. However, the tasks used in the few previous studies generally involved complex cognitive processes and rarely compared between patients with and without passivity experiences (PE). Here, we examined the deficits in internal motor predictive representation in patients with and without PE, and in healthy controls using a novel paradigm which involved minimal cognitive processes. All participants completed a modified joint position matching (mJPM) task, in which they were required to replicate a voluntary, a passive verbally-cued, and a passive tactile-cued movement under blinded conditions. The absolute difference between the target spot and replicated spot was measured and compared. We hypothesised that if there was a failure in the internal motor predictive representation, patients with PEs would replicate less accurately in the voluntary condition, relative to passive conditions while the healthy controls would be more accurate, and, therefore, significant interactions between groups and conditions would be revealed. Both healthy controls and patients without PEs replicated more accurately in the voluntary condition compared with the passive conditions. The patients with PEs were less accurate in the voluntary condition compared with the passive tactile condition. A significant interaction was observed between patients with vs. without PEs × voluntary vs. passive tactile conditions. The findings suggested the relationship between deficits in motor self-monitoring in the prediction process and PEs, thus showing the need to highlight the link between motor performance and PEs.
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Bethlehem RAI, Seidlitz J, White SR, Vogel JW, Anderson KM, Adamson C, Adler S, Alexopoulos GS, Anagnostou E, Areces-Gonzalez A, Astle DE, Auyeung B, Ayub M, Bae J, Ball G, Baron-Cohen S, Beare R, Bedford SA, Benegal V, Beyer F, Blangero J, Blesa Cábez M, Boardman JP, Borzage M, Bosch-Bayard JF, Bourke N, Calhoun VD, Chakravarty MM, Chen C, Chertavian C, Chetelat G, Chong YS, Cole JH, Corvin A, Costantino M, Courchesne E, Crivello F, Cropley VL, Crosbie J, Crossley N, Delarue M, Delorme R, Desrivieres S, Devenyi GA, Di Biase MA, Dolan R, Donald KA, Donohoe G, Dunlop K, Edwards AD, Elison JT, Ellis CT, Elman JA, Eyler L, Fair DA, Feczko E, Fletcher PC, Fonagy P, Franz CE, Galan-Garcia L, Gholipour A, Giedd J, Gilmore JH, Glahn DC, Goodyer IM, Grant PE, Groenewold NA, Gunning FM, Gur RE, Gur RC, Hammill CF, Hansson O, Hedden T, Heinz A, Henson RN, Heuer K, Hoare J, Holla B, Holmes AJ, Holt R, Huang H, Im K, Ipser J, Jack CR, Jackowski AP, Jia T, Johnson KA, Jones PB, Jones DT, Kahn RS, Karlsson H, Karlsson L, Kawashima R, Kelley EA, Kern S, Kim KW, Kitzbichler MG, Kremen WS, Lalonde F, Landeau B, Lee S, Lerch J, Lewis JD, Li J, Liao W, Liston C, Lombardo MV, Lv J, Lynch C, Mallard TT, Marcelis M, Markello RD, Mathias SR, Mazoyer B, McGuire P, Meaney MJ, Mechelli A, Medic N, Misic B, Morgan SE, Mothersill D, Nigg J, Ong MQW, Ortinau C, Ossenkoppele R, Ouyang M, Palaniyappan L, Paly L, Pan PM, Pantelis C, Park MM, Paus T, Pausova Z, Paz-Linares D, Pichet Binette A, Pierce K, Qian X, Qiu J, Qiu A, Raznahan A, Rittman T, Rodrigue A, Rollins CK, Romero-Garcia R, Ronan L, Rosenberg MD, Rowitch DH, Salum GA, Satterthwaite TD, Schaare HL, Schachar RJ, Schultz AP, Schumann G, Schöll M, Sharp D, Shinohara RT, Skoog I, Smyser CD, Sperling RA, Stein DJ, Stolicyn A, Suckling J, Sullivan G, Taki Y, Thyreau B, Toro R, Traut N, Tsvetanov KA, Turk-Browne NB, Tuulari JJ, Tzourio C, Vachon-Presseau É, Valdes-Sosa MJ, Valdes-Sosa PA, Valk SL, van Amelsvoort T, Vandekar SN, Vasung L, Victoria LW, Villeneuve S, Villringer A, Vértes PE, Wagstyl K, Wang YS, Warfield SK, Warrier V, Westman E, Westwater ML, Whalley HC, Witte AV, Yang N, Yeo B, Yun H, Zalesky A, Zar HJ, Zettergren A, Zhou JH, Ziauddeen H, Zugman A, Zuo XN, Bullmore ET, Alexander-Bloch AF. Brain charts for the human lifespan. Nature 2022; 604:525-533. [PMID: 35388223 PMCID: PMC9021021 DOI: 10.1038/s41586-022-04554-y] [Citation(s) in RCA: 462] [Impact Index Per Article: 231.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 02/16/2022] [Indexed: 02/02/2023]
Abstract
Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.
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Affiliation(s)
- R A I Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.
| | - J Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA.
| | - S R White
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - J W Vogel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Informatics & Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - K M Anderson
- Department of Psychology, Yale University, New Haven, CT, USA
| | - C Adamson
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Medicine, Monash University, Melbourne, Victoria, Australia
| | - S Adler
- UCL Great Ormond Street Institute for Child Health, London, UK
| | - G S Alexopoulos
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, USA
| | - E Anagnostou
- Department of Pediatrics University of Toronto, Toronto, Canada
- Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
| | - A Areces-Gonzalez
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
- University of Pinar del Río "Hermanos Saiz Montes de Oca", Pinar del Río, Cuba
| | - D E Astle
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - B Auyeung
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - M Ayub
- Queen's University, Department of Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canada
- University College London, Mental Health Neuroscience Research Department, Division of Psychiatry, London, UK
| | - J Bae
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
| | - G Ball
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia
| | - S Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridge Lifetime Asperger Syndrome Service (CLASS), Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - R Beare
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Medicine, Monash University, Melbourne, Victoria, Australia
| | - S A Bedford
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - V Benegal
- Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
| | - F Beyer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - J Blangero
- Department of Human Genetics, South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Edinburg, TX, USA
| | - M Blesa Cábez
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - J P Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - M Borzage
- Fetal and Neonatal Institute, Division of Neonatology, Children's Hospital Los Angeles, Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - J F Bosch-Bayard
- McGill Centre for Integrative Neuroscience, Ludmer Centre for Neuroinformatics and Mental Health, Montreal Neurological Institute, Montreal, Quebec, Canada
- McGill University, Montreal, Quebec, Canada
| | - N Bourke
- Department of Brain Sciences, Imperial College London, London, UK
- Care Research and Technology Centre, Dementia Research Institute, London, UK
| | - V D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - M M Chakravarty
- McGill University, Montreal, Quebec, Canada
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - C Chen
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - C Chertavian
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - G Chetelat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Y S Chong
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - J H Cole
- Centre for Medical Image Computing (CMIC), University College London, London, UK
- Dementia Research Centre (DRC), University College London, London, UK
| | - A Corvin
- Department of Psychiatry, Trinity College, Dublin, Ireland
| | - M Costantino
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Quebec, Canada
- Undergraduate program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - E Courchesne
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA
- Autism Center of Excellence, University of California, San Diego, San Diego, CA, USA
| | - F Crivello
- Institute of Neurodegenerative Disorders, CNRS UMR5293, CEA, University of Bordeaux, Bordeaux, France
| | - V L Cropley
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
| | - J Crosbie
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - N Crossley
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Instituto Milenio Intelligent Healthcare Engineering, Santiago, Chile
| | - M Delarue
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - R Delorme
- Child and Adolescent Psychiatry Department, Robert Debré University Hospital, AP-HP, Paris, France
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - S Desrivieres
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - G A Devenyi
- Cerebral Imaging Centre, McGill Department of Psychiatry, Douglas Mental Health University Institute, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M A Di Biase
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - R Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, London, UK
| | - K A Donald
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - G Donohoe
- Center for Neuroimaging, Cognition & Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - K Dunlop
- Weil Family Brain and Mind Research Institute, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - A D Edwards
- Centre for the Developing Brain, King's College London, London, UK
- Evelina London Children's Hospital, London, UK
- MRC Centre for Neurodevelopmental Disorders, London, UK
| | - J T Elison
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - C T Ellis
- Department of Psychology, Yale University, New Haven, CT, USA
- Haskins Laboratories, New Haven, CT, USA
| | - J A Elman
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - L Eyler
- Desert-Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, Los Angeles, CA, USA
| | - D A Fair
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - E Feczko
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - P C Fletcher
- Department of Psychiatry, University of Cambridge, and Wellcome Trust MRC Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - P Fonagy
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
- Anna Freud National Centre for Children and Families, London, UK
| | - C E Franz
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | | | - A Gholipour
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | - J Giedd
- Department of Child and Adolescent Psychiatry, University of California, San Diego, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - J H Gilmore
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - D C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - I M Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - P E Grant
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Groenewold
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, SA-MRC Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - F M Gunning
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - R E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - R C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - C F Hammill
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Mouse Imaging Centre, Toronto, Ontario, Canada
| | - O Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - T Hedden
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - A Heinz
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Berlin, Germany
| | - R N Henson
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - K Heuer
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Université de Paris, Paris, France
| | - J Hoare
- Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - B Holla
- Department of Integrative Medicine, NIMHANS, Bengaluru, India
- Accelerator Program for Discovery in Brain disorders using Stem cells (ADBS), Department of Psychiatry, NIMHANS, Bengaluru, India
| | - A J Holmes
- Departments of Psychology and Psychiatry, Yale University, New Haven, CT, USA
| | - R Holt
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - H Huang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- The Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - K Im
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - J Ipser
- Department of Psychiatry and Mental Health, Clinical Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - C R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - A P Jackowski
- Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, Brazil
- National Institute of Developmental Psychiatry, Beijing, China
| | - T Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and BrainInspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - K A Johnson
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - P B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - D T Jones
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - R S Kahn
- Department of Psychiatry, Icahn School of Medicine, Mount Sinai, NY, USA
| | - H Karlsson
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - L Karlsson
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - R Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - E A Kelley
- Queen's University, Departments of Psychology and Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canada
| | - S Kern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - K W Kim
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- Institute of Human Behavioral Medicine, SNU-MRC, Seoul, South Korea
| | - M G Kitzbichler
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - W S Kremen
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - F Lalonde
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - B Landeau
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - S Lee
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - J Lerch
- Mouse Imaging Centre, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - J D Lewis
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - J Li
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - W Liao
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - C Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - M V Lombardo
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - J Lv
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- School of Biomedical Engineering and Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - C Lynch
- Weil Family Brain and Mind Research Institute, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - T T Mallard
- Department of Psychology, University of Texas, Austin, TX, USA
| | - M Marcelis
- Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, Maastricht, The Netherlands
- Institute for Mental Health Care Eindhoven (GGzE), Eindhoven, The Netherlands
| | - R D Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - S R Mathias
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - B Mazoyer
- Institute of Neurodegenerative Disorders, CNRS UMR5293, CEA, University of Bordeaux, Bordeaux, France
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - P McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - M J Meaney
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - A Mechelli
- Bordeaux University Hospital, Bordeaux, France
| | - N Medic
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - B Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - S E Morgan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
| | - D Mothersill
- Department of Psychology, School of Business, National College of Ireland, Dublin, Ireland
- School of Psychology and Center for Neuroimaging and Cognitive Genomics, National University of Ireland Galway, Galway, Ireland
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - J Nigg
- Department of Psychiatry, School of Medicine, Oregon Health and Science University, Portland, OR, USA
| | - M Q W Ong
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - C Ortinau
- Department of Pediatrics, Washington University in St Louis, St Louis, MO, USA
| | - R Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Lund University, Clinical Memory Research Unit, Lund, Sweden
| | - M Ouyang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - L Palaniyappan
- Robarts Research Institute and The Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada
| | - L Paly
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - P M Pan
- Department of Psychiatry, Federal University of Sao Poalo (UNIFESP), Sao Poalo, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), Sao Poalo, Brazil
| | - C Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
- Melbourne School of Engineering, The University of Melbourne, Parkville, Victoria, Australia
- Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - M M Park
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - T Paus
- Department of Psychiatry, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
- Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Z Pausova
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - D Paz-Linares
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
- Cuban Neuroscience Center, Havana, Cuba
| | - A Pichet Binette
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - K Pierce
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA
| | - X Qian
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - J Qiu
- School of Psychology, Southwest University, Chongqing, China
| | - A Qiu
- Department of Biomedical Engineering, The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
| | - A Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - T Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - A Rodrigue
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - C K Rollins
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - R Romero-Garcia
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Instituto de Biomedicina de Sevilla (IBiS) HUVR/CSIC/Universidad de Sevilla, Dpto. de Fisiología Médica y Biofísica, Seville, Spain
| | - L Ronan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - M D Rosenberg
- Department of Psychology and Neuroscience Institute, University of Chicago, Chicago, IL, USA
| | - D H Rowitch
- Department of Paediatrics and Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - G A Salum
- Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Hospital de Clinicas de Porto Alegre, Porto Alegre, Brazil
- National Institute of Developmental Psychiatry (INPD), São Paulo, Brazil
| | - T D Satterthwaite
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Informatics & Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - H L Schaare
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Juelich, Juelich, Germany
| | - R J Schachar
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - A P Schultz
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - G Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Institute for Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
- PONS-Centre, Charite Mental Health, Dept of Psychiatry and Psychotherapy, Charite Campus Mitte, Berlin, Germany
| | - M Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Dementia Research Centre, Queen's Square Institute of Neurology, University College London, London, UK
| | - D Sharp
- Department of Brain Sciences, Imperial College London, London, UK
- Care Research and Technology Centre, UK Dementia Research Institute, London, UK
| | - R T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - I Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - C D Smyser
- Departments of Neurology, Pediatrics, and Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - R A Sperling
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - D J Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Dept of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - A Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - J Suckling
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - G Sullivan
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - Y Taki
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - B Thyreau
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - R Toro
- Université de Paris, Paris, France
- Department of Neuroscience, Institut Pasteur, Paris, France
| | - N Traut
- Department of Neuroscience, Institut Pasteur, Paris, France
- Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, France
| | - K A Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - N B Turk-Browne
- Department of Psychology, Yale University, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - J J Tuulari
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Medicine, University of Turku, Turku, Finland
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
| | - C Tzourio
- Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, U1219, CHU Bordeaux, Bordeaux, France
| | - É Vachon-Presseau
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada
| | | | - P A Valdes-Sosa
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
- Alan Edwards Centre for Research on Pain (AECRP), McGill University, Montreal, Quebec, Canada
| | - S L Valk
- Institute for Neuroscience and Medicine 7, Forschungszentrum Jülich, Jülich, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - T van Amelsvoort
- Department of Psychiatry and Neurosychology, Maastricht University, Maastricht, The Netherlands
| | - S N Vandekar
- Department of Biostatistics, Vanderbilt University, Nashville, TN, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - L Vasung
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - L W Victoria
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - S Villeneuve
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - A Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - P E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
| | - K Wagstyl
- Wellcome Centre for Human Neuroimaging, London, UK
| | - Y S Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - S K Warfield
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | - V Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - E Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - M L Westwater
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - H C Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - A V Witte
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany
- Faculty of Medicine, CRC 1052 'Obesity Mechanisms', University of Leipzig, Leipzig, Germany
| | - N Yang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - B Yeo
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Centre for Sleep and Cognition and Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine, National University of Singapore, Singapore, Singapore
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singapore
| | - H Yun
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - A Zalesky
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - H J Zar
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, SA-MRC Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - A Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
| | - J H Zhou
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Center for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - H Ziauddeen
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - A Zugman
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), Sao Poalo, Brazil
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Psychiatry, Escola Paulista de Medicina, São Paulo, Brazil
| | - X N Zuo
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Brain and Education, School of Education Science, Nanning Normal University, Nanning, China
| | - E T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - A F Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
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Ryan MC, Hong LE, Hatch KS, Gao S, Chen S, Haerian K, Wang J, Goldwaser EL, Du X, Adhikari BM, Bruce H, Hare S, Kvarta MD, Jahanshad N, Nichols TE, Thompson PM, Kochunov P. The additive impact of cardio-metabolic disorders and psychiatric illnesses on accelerated brain aging. Hum Brain Mapp 2022; 43:1997-2010. [PMID: 35112422 PMCID: PMC8933252 DOI: 10.1002/hbm.25769] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Revised: 11/28/2021] [Accepted: 12/28/2021] [Indexed: 12/24/2022] Open
Abstract
Severe mental illnesses (SMI) including major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorder (SSD) elevate accelerated brain aging risks. Cardio‐metabolic disorders (CMD) are common comorbidities in SMI and negatively impact brain health. We validated a linear quantile regression index (QRI) approach against the machine learning “BrainAge” index in an independent SSD cohort (N = 206). We tested the direct and additive effects of SMI and CMD effects on accelerated brain aging in the N = 1,618 (604 M/1,014 F, average age = 63.53 ± 7.38) subjects with SMI and N = 11,849 (5,719 M/6,130 F; 64.42 ± 7.38) controls from the UK Biobank. Subjects were subdivided based on diagnostic status: SMI+/CMD+ (N = 665), SMI+/CMD− (N = 964), SMI−/CMD+ (N = 3,765), SMI−/CMD− (N = 8,083). SMI (F = 40.47, p = 2.06 × 10−10) and CMD (F = 24.69, p = 6.82 × 10−7) significantly, independently impacted whole‐brain QRI in SMI+. SSD had the largest effect (Cohen’s d = 1.42) then BD (d = 0.55), and MDD (d = 0.15). Hypertension had a significant effect on SMI+ (d = 0.19) and SMI− (d = 0.14). SMI effects were direct, independent of MD, and remained significant after correcting for effects of antipsychotic medications. Whole‐brain QRI was significantly (p < 10−16) associated with the volume of white matter hyperintensities (WMH). However, WMH did not show significant association with SMI and was driven by CMD, chiefly hypertension (p < 10−16). We used a simple and robust index, QRI, the demonstrate additive effect of SMI and CMD on accelerated brain aging. We showed a greater effect of psychiatric illnesses on QRI compared to cardio‐metabolic illness. Our findings suggest that subjects with SMI should be among the targets for interventions to protect against age‐related cognitive decline.
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Affiliation(s)
- Meghann C Ryan
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - L Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Kathryn S Hatch
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Si Gao
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Shuo Chen
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA.,Division of Biostatistics and Bioinformatics, Department of Public Health and Epidemiology, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Krystl Haerian
- Department of Clinical Research and Leadership, School of Medicine and Health Sciences, George Washington University, Washington, District of Columbia, USA
| | - Jingtao Wang
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA.,Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Eric L Goldwaser
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Xiaoming Du
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Bhim M Adhikari
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Heather Bruce
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Stephanie Hare
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Mark D Kvarta
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Los Angeles, California, USA
| | - Thomas E Nichols
- Nuffield Department of Population Health of the University of Oxford, Oxford, UK
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Los Angeles, California, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
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38
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Bann D, Wright L, Cole TJ. Risk factors relate to the variability of health outcomes as well as the mean: A GAMLSS tutorial. eLife 2022; 11:72357. [PMID: 34985412 PMCID: PMC8791632 DOI: 10.7554/elife.72357] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 01/04/2022] [Indexed: 01/03/2023] Open
Abstract
Background: Risk factors or interventions may affect the variability as well as the mean of health outcomes. Understanding this can aid aetiological understanding and public health translation, in that interventions which shift the outcome mean and reduce variability are typically preferable to those which affect only the mean. However, most commonly used statistical tools do not test for differences in variability. Tools that do have few epidemiological applications to date, and fewer applications still have attempted to explain their resulting findings. We thus provide a tutorial for investigating this using GAMLSS (Generalised Additive Models for Location, Scale and Shape). Methods: The 1970 British birth cohort study was used, with body mass index (BMI; N = 6007) and mental wellbeing (Warwick-Edinburgh Mental Wellbeing Scale; N = 7104) measured in midlife (42–46 years) as outcomes. We used GAMLSS to investigate how multiple risk factors (sex, childhood social class, and midlife physical inactivity) related to differences in health outcome mean and variability. Results: Risk factors were related to sizable differences in outcome variability—for example males had marginally higher mean BMI yet 28% lower variability; lower social class and physical inactivity were each associated with higher mean and higher variability (6.1% and 13.5% higher variability, respectively). For mental wellbeing, gender was not associated with the mean while males had lower variability (–3.9%); lower social class and physical inactivity were each associated with lower mean yet higher variability (7.2% and 10.9% higher variability, respectively). Conclusions: The results highlight how GAMLSS can be used to investigate how risk factors or interventions may influence the variability in health outcomes. This underutilised approach to the analysis of continuously distributed outcomes may have broader utility in epidemiologic, medical, and psychological sciences. A tutorial and replication syntax is provided online to facilitate this (https://osf.io/5tvz6/). Funding: DB is supported by the Economic and Social Research Council (grant number ES/M001660/1), The Academy of Medical Sciences / Wellcome Trust (“Springboard Health of the Public in 2040” award: HOP001/1025); DB and LW are supported by the Medical Research Council (MR/V002147/1). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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Affiliation(s)
- David Bann
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, United Kingdom
| | - Liam Wright
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, United Kingdom
| | - Tim J Cole
- Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
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39
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Turner JA, Calhoun VD, Thompson PM, Jahanshad N, Ching CRK, Thomopoulos SI, Verner E, Strauss GP, Ahmed AO, Turner MD, Basodi S, Ford JM, Mathalon DH, Preda A, Belger A, Mueller BA, Lim KO, van Erp TGM. ENIGMA + COINSTAC: Improving Findability, Accessibility, Interoperability, and Re-usability. Neuroinformatics 2022; 20:261-275. [PMID: 34846691 PMCID: PMC9149142 DOI: 10.1007/s12021-021-09559-y] [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] [Accepted: 11/19/2021] [Indexed: 01/07/2023]
Abstract
The FAIR principles, as applied to clinical and neuroimaging data, reflect the goal of making research products Findable, Accessible, Interoperable, and Reusable. The use of the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymized Computation (COINSTAC) platform in the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium combines the technological approach of decentralized analyses with the sociological approach of sharing data. In addition, ENIGMA + COINSTAC provides a platform to facilitate the use of machine-actionable data objects. We first present how ENIGMA and COINSTAC support the FAIR principles, and then showcase their integration with a decentralized meta-analysis of sex differences in negative symptom severity in schizophrenia, and finally present ongoing activities and plans to advance FAIR principles in ENIGMA + COINSTAC. ENIGMA and COINSTAC currently represent efforts toward improved Access, Interoperability, and Reusability. We highlight additional improvements needed in these areas, as well as future connections to other resources for expanded Findability.
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Affiliation(s)
- Jessica A Turner
- Psychology Department, Georgia State University, Atlanta, GA, USA.
| | - Vince D Calhoun
- Psychology Department, Georgia State University, Atlanta, GA, USA
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, 30303, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Christopher R K Ching
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Eric Verner
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, 30303, USA
| | - Gregory P Strauss
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - Anthony O Ahmed
- Weill Cornell Medicine, Department of Psychiatry, White Plains, NY, 10605, USA
| | - Matthew D Turner
- Psychology Department, Georgia State University, Atlanta, GA, USA
| | - Sunitha Basodi
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, 30303, USA
| | - Judith M Ford
- Veterans Affairs San Francisco Healthcare System, San Francisco, CA, 94121, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, 94121, USA
| | - Daniel H Mathalon
- Veterans Affairs San Francisco Healthcare System, San Francisco, CA, 94121, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, 94121, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, University of California Irvine Medical Center, 101 The City Drive S, Orange, CA, 92868, USA
| | - Aysenil Belger
- Department of Psychiatry and Frank Porter Graham Child Development Institute, University of North Carolina at Chapel Hill, 105 Smith Level Road, Chapel Hill, NC, 27599-8180, USA
| | - Bryon A Mueller
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Kelvin O Lim
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, 5251 California Ave, Irvine, CA, 92617, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, 92697, USA
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40
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Salminen LE, Tubi MA, Bright J, Thomopoulos SI, Wieand A, Thompson PM. Sex is a defining feature of neuroimaging phenotypes in major brain disorders. Hum Brain Mapp 2022; 43:500-542. [PMID: 33949018 PMCID: PMC8805690 DOI: 10.1002/hbm.25438] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 12/12/2022] Open
Abstract
Sex is a biological variable that contributes to individual variability in brain structure and behavior. Neuroimaging studies of population-based samples have identified normative differences in brain structure between males and females, many of which are exacerbated in psychiatric and neurological conditions. Still, sex differences in MRI outcomes are understudied, particularly in clinical samples with known sex differences in disease risk, prevalence, and expression of clinical symptoms. Here we review the existing literature on sex differences in adult brain structure in normative samples and in 14 distinct psychiatric and neurological disorders. We discuss commonalities and sources of variance in study designs, analysis procedures, disease subtype effects, and the impact of these factors on MRI interpretation. Lastly, we identify key problems in the neuroimaging literature on sex differences and offer potential recommendations to address current barriers and optimize rigor and reproducibility. In particular, we emphasize the importance of large-scale neuroimaging initiatives such as the Enhancing NeuroImaging Genetics through Meta-Analyses consortium, the UK Biobank, Human Connectome Project, and others to provide unprecedented power to evaluate sex-specific phenotypes in major brain diseases.
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Affiliation(s)
- Lauren E. Salminen
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Meral A. Tubi
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Joanna Bright
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Sophia I. Thomopoulos
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Alyssa Wieand
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics CenterMark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
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41
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Frangou S, Modabbernia A, Williams SCR, Papachristou E, Doucet GE, Agartz I, Aghajani M, Akudjedu TN, Albajes‐Eizagirre A, Alnæs D, Alpert KI, Andersson M, Andreasen NC, Andreassen OA, Asherson P, Banaschewski T, Bargallo N, Baumeister S, Baur‐Streubel R, Bertolino A, Bonvino A, Boomsma DI, Borgwardt S, Bourque J, Brandeis D, Breier A, Brodaty H, Brouwer RM, Buitelaar JK, Busatto GF, Buckner RL, Calhoun V, Canales‐Rodríguez EJ, Cannon DM, Caseras X, Castellanos FX, Cervenka S, Chaim‐Avancini TM, Ching CRK, Chubar V, Clark VP, Conrod P, Conzelmann A, Crespo‐Facorro B, Crivello F, Crone EA, Dale AM, Dannlowski U, Davey C, de Geus EJC, de Haan L, de Zubicaray GI, den Braber A, Dickie EW, Di Giorgio A, Doan NT, Dørum ES, Ehrlich S, Erk S, Espeseth T, Fatouros‐Bergman H, Fisher SE, Fouche J, Franke B, Frodl T, Fuentes‐Claramonte P, Glahn DC, Gotlib IH, Grabe H, Grimm O, Groenewold NA, Grotegerd D, Gruber O, Gruner P, Gur RE, Gur RC, Hahn T, Harrison BJ, Hartman CA, Hatton SN, Heinz A, Heslenfeld DJ, Hibar DP, Hickie IB, Ho B, Hoekstra PJ, Hohmann S, Holmes AJ, Hoogman M, Hosten N, Howells FM, Hulshoff Pol HE, Huyser C, Jahanshad N, James A, Jernigan TL, Jiang J, Jönsson EG, Joska JA, Kahn R, Kalnin A, Kanai R, Klein M, Klyushnik TP, Koenders L, Koops S, Krämer B, Kuntsi J, Lagopoulos J, Lázaro L, Lebedeva I, Lee WH, Lesch K, Lochner C, Machielsen MWJ, Maingault S, Martin NG, Martínez‐Zalacaín I, Mataix‐Cols D, Mazoyer B, McDonald C, McDonald BC, McIntosh AM, McMahon KL, McPhilemy G, Meinert S, Menchón JM, Medland SE, Meyer‐Lindenberg A, Naaijen J, Najt P, Nakao T, Nordvik JE, Nyberg L, Oosterlaan J, de la Foz VO, Paloyelis Y, Pauli P, Pergola G, Pomarol‐Clotet E, Portella MJ, Potkin SG, Radua J, Reif A, Rinker DA, Roffman JL, Rosa PGP, Sacchet MD, Sachdev PS, Salvador R, Sánchez‐Juan P, Sarró S, Satterthwaite TD, Saykin AJ, Serpa MH, Schmaal L, Schnell K, Schumann G, Sim K, Smoller JW, Sommer I, Soriano‐Mas C, Stein DJ, Strike LT, Swagerman SC, Tamnes CK, Temmingh HS, Thomopoulos SI, Tomyshev AS, Tordesillas‐Gutiérrez D, Trollor JN, Turner JA, Uhlmann A, van den Heuvel OA, van den Meer D, van der Wee NJA, van Haren NEM, van 't Ent D, van Erp TGM, Veer IM, Veltman DJ, Voineskos A, Völzke H, Walter H, Walton E, Wang L, Wang Y, Wassink TH, Weber B, Wen W, West JD, Westlye LT, Whalley H, Wierenga LM, Wittfeld K, Wolf DH, Worker A, Wright MJ, Yang K, Yoncheva Y, Zanetti MV, Ziegler GC, Thompson PM, Dima D. Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years. Hum Brain Mapp 2022; 43:431-451. [PMID: 33595143 PMCID: PMC8675431 DOI: 10.1002/hbm.25364] [Citation(s) in RCA: 103] [Impact Index Per Article: 51.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 01/02/2021] [Accepted: 01/21/2021] [Indexed: 12/25/2022] Open
Abstract
Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
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Affiliation(s)
- Sophia Frangou
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew York CityNew YorkUSA
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain HealthUniversity of British ColumbiaVancouverCanada
| | | | - Steven C. R. Williams
- Department of NeuroimagingInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
| | - Efstathios Papachristou
- Psychology and Human DevelopmentInstitute of Education, University College LondonLondonUnited Kingdom
| | - Gaelle E. Doucet
- Institute for Human NeuroscienceBoys Town National Research HospitalOmahaNebraskaUSA
| | - Ingrid Agartz
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetSolnaSweden
| | - Moji Aghajani
- Department of PsychiatryAmsterdam University Medical Centre, Vrije UniversiteitAmsterdamNetherlands
- Section Forensic Family & Youth CareInstitute of Education & Child StudiesLeiden UniversityNetherlands
| | - Theophilus N. Akudjedu
- Institute of Medical Imaging and Visualisation, Department of Medical Science and Public Health, Faculty of Health and Social SciencesBournemouth UniversityPooleUnited Kingdom
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandGalwayIreland
| | - Anton Albajes‐Eizagirre
- FIDMAG Germanes HospitalàriesBarcelonaSpain
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
- Division of Mental Health and AddictionInstitute of Clinical Medicine, University of OsloOsloNorway
| | | | - Micael Andersson
- Department of Integrative Medical BiologyUmeå UniversityUmeåSweden
| | - Nancy C. Andreasen
- Department of Psychiatry, Carver College of MedicineThe University of IowaIowa CityIowaUSA
| | - Ole A. Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
| | - Philip Asherson
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental HealthHeidelberg UniversityHeidelbergGermany
| | - Nuria Bargallo
- Imaging Diagnostic CentreHospital Clinic, Barcelona University ClinicBarcelonaSpain
- August Pi i Sunyer Biomedical Research Institut (IDIBAPS)BarcelonaSpain
| | - Sarah Baumeister
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental HealthHeidelberg UniversityHeidelbergGermany
| | - Ramona Baur‐Streubel
- Department of Psychology, Biological Psychology, Clinical Psychology and PsychotherapyUniversity of WürzburgWürzburgGermany
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari Aldo MoroBariItaly
| | - Aurora Bonvino
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Dorret I. Boomsma
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Stefan Borgwardt
- Department of Psychiatry & PsychotherapyUniversity of LübeckLübeckGermany
| | - Josiane Bourque
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Daniel Brandeis
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental HealthHeidelberg UniversityHeidelbergGermany
| | - Alan Breier
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesKensingtonNew South WalesAustralia
| | - Rachel M. Brouwer
- Rudolf Magnus Institute of NeuroscienceUniversity Medical Center UtrechtUtrechtNetherlands
| | - Jan K. Buitelaar
- Donders Center of Medical NeurosciencesRadboud UniversityNijmegenNetherlands
- Donders Centre for Cognitive NeuroimagingRadboud UniversityNijmegenNetherlands
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
| | - Geraldo F. Busatto
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
| | - Randy L. Buckner
- Department of Psychology, Center for Brain ScienceHarvard UniversityCambridgeMassachusettsUSA
- Department of PsychiatryMassachusetts General HospitalBostonMassachusettsUSA
| | - Vincent Calhoun
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of TechnologyEmory University, USA Neurology, Radiology, Psychiatry and Biomedical Engineering, Emory UniversityAtlantaGeorgiaUSA
| | - Erick J. Canales‐Rodríguez
- FIDMAG Germanes HospitalàriesBarcelonaSpain
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
| | - Dara M. Cannon
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandGalwayIreland
| | - Xavier Caseras
- MRC Centre for Neuropsychiatric Genetics and GenomicsCardiff UniversityCardiffUnited Kingdom
| | | | - Simon Cervenka
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetSolnaSweden
- Stockholm Health Care ServicesStockholmSweden
| | - Tiffany M. Chaim‐Avancini
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
| | - Christopher R. K. Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Victoria Chubar
- Mind‐Body Research Group, Department of NeuroscienceKU LeuvenLeuvenBelgium
| | - Vincent P. Clark
- Department of PsychologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
- Mind Research NetworkAlbuquerqueNew MexicoUSA
| | - Patricia Conrod
- Department of PsychiatryUniversité de MontréalMontrealCanada
| | - Annette Conzelmann
- Department of Child and Adolescent Psychiatry, Psychosomatics and PsychotherapyUniversity of TübingenTübingenGermany
| | - Benedicto Crespo‐Facorro
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- HU Virgen del Rocio, IBiSUniversity of SevillaSevillaSpain
| | - Fabrice Crivello
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293Université de BordeauxBordeauxFrance
| | - Eveline A. Crone
- Erasmus School of Social and Behavioural SciencesErasmus University RotterdamRotterdamNetherlands
- Faculteit der Sociale Wetenschappen, Instituut PsychologieUniversiteit LeidenLeidenNetherlands
| | - Anders M. Dale
- Center for Multimodal Imaging and Genetics, Department of NeuroscienceUniversity of California‐San DiegoSan DiegoCaliforniaUSA
- Department of RadiologyUniversity of California‐San DiegoSan DiegoCaliforniaUSA
| | - Udo Dannlowski
- Department of Psychiatry and PsychotherapyUniversity of MünsterGermany
| | | | - Eco J. C. de Geus
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Lieuwe de Haan
- Academisch Medisch CentrumUniversiteit van AmsterdamAmsterdamNetherlands
| | - Greig I. de Zubicaray
- Faculty of Health, Institute of Health and Biomedical InnovationQueensland University of TechnologyQueenslandAustralia
| | - Anouk den Braber
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Erin W. Dickie
- Kimel Family Translational Imaging Genetics Laboratory, Campbell Family Mental Health Research InstituteCAMHCampbellCanada
- Department of PsychiatryUniversity of TorontoTorontoCanada
| | - Annabella Di Giorgio
- Biological Psychiatry LabFondazione IRCCS Casa Sollievo della SofferenzaSan Giovanni Rotondo (FG)Italy
| | - Nhat Trung Doan
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
| | - Erlend S. Dørum
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
- Department of PsychologyUniversity of OsloOsloNorway
- Sunnaas Rehabilitation Hospital HTNesoddenNorway
| | - Stefan Ehrlich
- Division of Psychological and Social Medicine and Developmental NeurosciencesTechnische Universität DresdenDresdenGermany
- Faculty of MedicineUniversitätsklinikum Carl Gustav Carus an der TU DresdenDresdenGermany
| | - Susanne Erk
- Division of Mind and Brain Research, Department of Psychiatry and PsychotherapyCharité‐Universitätsmedizin BerlinBerlinGermany
| | - Thomas Espeseth
- Biological Psychiatry LabFondazione IRCCS Casa Sollievo della SofferenzaSan Giovanni Rotondo (FG)Italy
- Bjørknes CollegeOsloNorway
| | - Helena Fatouros‐Bergman
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetSolnaSweden
- Stockholm Health Care ServicesStockholmSweden
| | - Simon E. Fisher
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenNetherlands
| | - Jean‐Paul Fouche
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
| | - Barbara Franke
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
- Department of Human GeneticsRadboud University Medical CenterNijmegenNetherlands
- Department of PsychiatryRadboud University Medical CenterNijmegenNetherlands
| | - Thomas Frodl
- Department of Psychiatry and PsychotherapyOtto von Guericke University MagdeburgMagdeburgGermany
| | - Paola Fuentes‐Claramonte
- FIDMAG Germanes HospitalàriesBarcelonaSpain
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
| | - David C. Glahn
- Department of PsychiatryTommy Fuss Center for Neuropsychiatric Disease Research Boston Children's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Ian H. Gotlib
- Department of PsychologyStanford UniversityStanfordCaliforniaUSA
| | - Hans‐Jörgen Grabe
- Department of Psychiatry and PsychotherapyUniversity Medicine Greifswald, University of GreifswaldGreifswaldGermany
- German Center for Neurodegenerative Diseases (DZNE)Site Rostock/GreifswaldGreifswaldGermany
| | - Oliver Grimm
- Department for Psychiatry, Psychosomatics and PsychotherapyUniversitätsklinikum Frankfurt, Goethe UniversitatFrankfurtGermany
| | - Nynke A. Groenewold
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
- Neuroscience InstituteUniversity of Cape TownCape TownSouth Africa
| | | | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryHeidelberg UniversityHeidelbergGermany
| | - Patricia Gruner
- Department of PsychiatryYale UniversityNew HavenConnecticutUSA
- Learning Based Recovery CenterVA Connecticut Health SystemWest HavenConnecticutUSA
| | - Rachel E. Gur
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Lifespan Brain Institute, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Children's Hospital of PhiladelphiaUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Ruben C. Gur
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Lifespan Brain Institute, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Children's Hospital of PhiladelphiaUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Tim Hahn
- Department of Psychiatry and PsychotherapyUniversity of MünsterGermany
| | - Ben J. Harrison
- Melbourne Neuropsychiatry CenterUniversity of MelbourneMelbourneAustralia
| | - Catharine A. Hartman
- Interdisciplinary Center Psychopathology and Emotion regulationUniversity Medical Center Groningen, University of GroningenGroningenNetherlands
| | - Sean N. Hatton
- Brain and Mind CentreUniversity of SydneySydneyAustralia
| | - Andreas Heinz
- Division of Mind and Brain Research, Department of Psychiatry and PsychotherapyCharité‐Universitätsmedizin BerlinBerlinGermany
| | - Dirk J. Heslenfeld
- Departments of Experimental and Clinical PsychologyVrije Universiteit AmsterdamAmsterdamNetherlands
| | - Derrek P. Hibar
- Personalized Healthcare, Genentech, Inc.South San FranciscoCaliforniaUSA
| | - Ian B. Hickie
- Brain and Mind CentreUniversity of SydneySydneyAustralia
| | - Beng‐Choon Ho
- Department of Psychiatry, Carver College of MedicineThe University of IowaIowa CityIowaUSA
| | - Pieter J. Hoekstra
- Department of PsychiatryUniversity Medical Center Groningen, University of GroningenGroningenNetherlands
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental HealthHeidelberg UniversityHeidelbergGermany
| | - Avram J. Holmes
- Department of PsychologyYale UniversityNew HavenConnecticutUSA
| | - Martine Hoogman
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
- Department of Human GeneticsRadboud University Medical CenterNijmegenNetherlands
| | - Norbert Hosten
- Norbert Institute of Diagnostic Radiology and NeuroradiologyUniversity Medicine Greifswald, University of GreifswaldGreifswaldGermany
| | - Fleur M. Howells
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
- Neuroscience InstituteUniversity of Cape TownCape TownSouth Africa
| | | | - Chaim Huyser
- De Bascule, Academic Centre for Children and Adolescent PsychiatryAmsterdamNetherlands
| | - Neda Jahanshad
- Mind‐Body Research Group, Department of NeuroscienceKU LeuvenLeuvenBelgium
| | - Anthony James
- Department of PsychiatryOxford UniversityOxfordUnited Kingdom
| | - Terry L. Jernigan
- Center for Human Development, Departments of Cognitive Science, Psychiatry, and RadiologyUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesKensingtonNew South WalesAustralia
| | - Erik G. Jönsson
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
| | - John A. Joska
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
| | - Rene Kahn
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew York CityNew YorkUSA
| | - Andrew Kalnin
- Department of RadiologyOhio State University College of MedicineColumbusOhioUSA
| | - Ryota Kanai
- Department of NeuroinformaticsAraya, Inc.TokyoJapan
| | - Marieke Klein
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
- Department of Human GeneticsRadboud University Medical CenterNijmegenNetherlands
- Department of PsychiatryUniversity of California San DiegoSan DiegoCaliforniaUSA
| | | | - Laura Koenders
- Academisch Medisch CentrumUniversiteit van AmsterdamAmsterdamNetherlands
| | - Sanne Koops
- Rudolf Magnus Institute of NeuroscienceUniversity Medical Center UtrechtUtrechtNetherlands
| | - Bernd Krämer
- Section for Experimental Psychopathology and Neuroimaging, Department of General PsychiatryHeidelberg UniversityHeidelbergGermany
| | - Jonna Kuntsi
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
| | - Jim Lagopoulos
- Sunshine Coast Mind and NeuroscienceThompson Institute, University of the Sunshine CoastQueenslandAustralia
| | - Luisa Lázaro
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of Child and Adolescent Psychiatry and PsychologyHospital Clinic, University of BarcelonaBarcelonaSpain
| | - Irina Lebedeva
- Mental Health Research CenterRussian Academy of Medical SciencesMoscowRussia
| | - Won Hee Lee
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew York CityNew YorkUSA
| | - Klaus‐Peter Lesch
- Department of Psychiatry, Psychosomatics and PsychotherapyJulius‐Maximilians Universität WürzburgWürzburgGermany
| | - Christine Lochner
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of PsychiatryStellenbosch UniversityStellenboschSouth Africa
| | | | - Sophie Maingault
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293Université de BordeauxBordeauxFrance
| | - Nicholas G. Martin
- Queensland Institute of Medical ResearchBerghofer Medical Research InstituteQueenslandAustralia
| | - Ignacio Martínez‐Zalacaín
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of PsychiatryBellvitge University Hospital‐IDIBELL, University of BarcelonaBarcelonaSpain
| | - David Mataix‐Cols
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetSolnaSweden
- Stockholm Health Care ServicesStockholmSweden
| | - Bernard Mazoyer
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293Université de BordeauxBordeauxFrance
| | - Colm McDonald
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandGalwayIreland
| | - Brenna C. McDonald
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | | | - Katie L. McMahon
- School of Clinical Sciences, Institute of Health and Biomedical InnovationQueensland University of TechnologyQueenslandAustralia
| | - Genevieve McPhilemy
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandGalwayIreland
| | - Susanne Meinert
- Department of Psychiatry and PsychotherapyUniversity of MünsterGermany
| | - José M. Menchón
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of PsychiatryBellvitge University Hospital‐IDIBELL, University of BarcelonaBarcelonaSpain
| | - Sarah E. Medland
- Queensland Institute of Medical ResearchBerghofer Medical Research InstituteQueenslandAustralia
| | - Andreas Meyer‐Lindenberg
- Department of Psychiatry and PsychotherapyCentral Institute of Mental Health, Heidelberg UniversityHeidelbergGermany
| | - Jilly Naaijen
- Donders Centre for Cognitive NeuroimagingRadboud UniversityNijmegenNetherlands
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenNetherlands
| | - Pablo Najt
- Clinical Neuroimaging Laboratory, Centre for Neuroimaging and Cognitive Genomics and NCBES Galway Neuroscience CentreNational University of IrelandGalwayIreland
| | - Tomohiro Nakao
- Department of Clinical MedicineKyushu UniversityFukuokaJapan
| | | | - Lars Nyberg
- Department of Integrative Medical BiologyUmeå UniversityUmeåSweden
- Department of Radiation SciencesUmeå Center for Functional Brain Imaging, Umeå UniversityUmeåSweden
| | - Jaap Oosterlaan
- Department of Clinical NeuropsychologyAmsterdam University Medical Centre, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Víctor Ortiz‐García de la Foz
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of PsychiatryUniversity Hospital “Marques de Valdecilla”, Instituto de Investigación Valdecilla (IDIVAL)SantanderSpain
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM)Instituto de Salud Carlos IIIMadridSpain
| | - Yannis Paloyelis
- Department of NeuroimagingInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
| | - Paul Pauli
- Department of Psychology, Biological Psychology, Clinical Psychology and PsychotherapyUniversity of WürzburgWürzburgGermany
- Centre of Mental HealthUniversity of WürzburgWürzburgGermany
| | - Giulio Pergola
- Department of Basic Medical Science, Neuroscience and Sense OrgansUniversity of Bari Aldo MoroBariItaly
| | - Edith Pomarol‐Clotet
- FIDMAG Germanes HospitalàriesBarcelonaSpain
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
| | - Maria J. Portella
- FIDMAG Germanes HospitalàriesBarcelonaSpain
- Department of PsychiatryHospital de la Santa Creu i Sant Pau, Institut d'Investigació Biomèdica Sant Pau, Universitat Autònoma de BarcelonaBarcelonaSpain
| | - Steven G. Potkin
- Department of PsychiatryUniversity of California at IrvineIrvineCaliforniaUSA
| | - Joaquim Radua
- Centre for Psychiatric Research, Department of Clinical NeuroscienceKarolinska InstitutetSolnaSweden
- August Pi i Sunyer Biomedical Research Institut (IDIBAPS)BarcelonaSpain
- Department of Psychosis StudiesInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonLondonUnited Kingdom
| | - Andreas Reif
- Department for Psychiatry, Psychosomatics and PsychotherapyUniversitätsklinikum Frankfurt, Goethe UniversitatFrankfurtGermany
| | - Daniel A. Rinker
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
| | - Joshua L. Roffman
- Department of PsychiatryMassachusetts General HospitalBostonMassachusettsUSA
| | - Pedro G. P. Rosa
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
| | - Matthew D. Sacchet
- Center for Depression, Anxiety, and Stress ResearchMcLean Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesKensingtonNew South WalesAustralia
| | | | - Pascual Sánchez‐Juan
- Department of PsychiatryUniversity Hospital “Marques de Valdecilla”, Instituto de Investigación Valdecilla (IDIVAL)SantanderSpain
- Centro de Investigacion Biomedica en Red en Enfermedades Neurodegenerativas (CIBERNED)ValderrebolloSpain
| | | | | | - Andrew J. Saykin
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | - Mauricio H. Serpa
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
| | - Lianne Schmaal
- OrygenThe National Centre of Excellence in Youth Mental HealthMelbourneAustralia
- Centre for Youth Mental HealthThe University of MelbourneMelbourneAustralia
| | - Knut Schnell
- Department of Psychiatry and PsychotherapyUniversity Medical Center GöttingenGöttingenGermany
| | - Gunter Schumann
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
- Centre for Population Neuroscience and Precision MedicineInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonLondonUnited Kingdom
| | - Kang Sim
- Department of General PsychiatryInstitute of Mental HealthSingaporeSingapore
| | - Jordan W. Smoller
- Center for Genomic MedicineMassachusetts General HospitalBostonMassachusettsUSA
| | - Iris Sommer
- Department of Biomedical Sciences of Cells and Systems, Rijksuniversiteit GroningenUniversity Medical Center GroningenGroningenNetherlands
| | - Carles Soriano‐Mas
- Mental Health Research Networking Center (CIBERSAM)MadridSpain
- Department of PsychiatryBellvitge University Hospital‐IDIBELL, University of BarcelonaBarcelonaSpain
| | - Dan J. Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of PsychiatryStellenbosch UniversityStellenboschSouth Africa
| | - Lachlan T. Strike
- Queensland Brain InstituteUniversity of QueenslandQueenslandAustralia
| | | | - Christian K. Tamnes
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
- Department of Psychiatric ResearchDiakonhjemmet HospitalOsloNorway
- PROMENTA Research Center, Department of PsychologyUniversity of OsloOsloNorway
| | - Henk S. Temmingh
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | | | - Diana Tordesillas‐Gutiérrez
- FIDMAG Germanes HospitalàriesBarcelonaSpain
- Neuroimaging Unit, Technological FacilitiesValdecilla Biomedical Research Institute IDIVALCantabriaSpain
| | - Julian N. Trollor
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesKensingtonNew South WalesAustralia
| | - Jessica A. Turner
- College of Arts and SciencesGeorgia State UniversityAtlantaGeorgiaUSA
| | - Anne Uhlmann
- Department of Psychiatry and Mental HealthUniversity of Cape TownCape TownSouth Africa
| | - Odile A. van den Heuvel
- Department of PsychiatryAmsterdam University Medical Centre, Vrije UniversiteitAmsterdamNetherlands
| | - Dennis van den Meer
- Norwegian Centre for Mental Disorders Research (NORMENT)Institute of Clinical Medicine, University of OsloOsloNorway
- Division of Mental Health and AddictionInstitute of Clinical Medicine, University of OsloOsloNorway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life SciencesMaastricht UniversityMaastrichtNetherlands
| | - Nic J. A. van der Wee
- Department of PsychiatryLeiden University Medical CenterLeidenNetherlands
- Leiden Institute for Brain and CognitionLeiden University Medical CenterLeidenNetherlands
| | - Neeltje E. M. van Haren
- Department of Child and Adolescent Psychiatry/PsychologyErasmus University Medical Center, Sophia Children's HospitalRotterdamThe Netherlands
| | - Dennis van 't Ent
- Department of Biological PsychologyVrije UniversiteitAmsterdamNetherlands
| | - Theo G. M. van Erp
- Department of PsychiatryUniversity of California at IrvineIrvineCaliforniaUSA
- Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA
- Institute of Community MedicineUniversity Medicine, Greifswald, University of GreifswaldGreifswaldGermany
| | - Ilya M. Veer
- Division of Mind and Brain Research, Department of Psychiatry and PsychotherapyCharité‐Universitätsmedizin BerlinBerlinGermany
| | - Dick J. Veltman
- Department of PsychiatryAmsterdam University Medical Centre, Vrije UniversiteitAmsterdamNetherlands
| | - Aristotle Voineskos
- Kimel Family Translational Imaging Genetics Laboratory, Campbell Family Mental Health Research InstituteCAMHCampbellCanada
- Department of PsychiatryUniversity of TorontoTorontoCanada
| | - Henry Völzke
- Institute of Community MedicineUniversity Medicine, Greifswald, University of GreifswaldGreifswaldGermany
- German Centre for Cardiovascular Research (DZHK), partner site GreifswaldGreifswaldGermany
- German Center for Diabetes Research (DZD), partner site GreifswaldGreifswaldGermany
| | - Henrik Walter
- Division of Mind and Brain Research, Department of Psychiatry and PsychotherapyCharité‐Universitätsmedizin BerlinBerlinGermany
| | - Esther Walton
- Department of PsychologyUniversity of BathBathUnited Kingdom
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Feinberg School of MedicineNorthwestern UniversityEvanstonIllinoisUSA
| | - Yang Wang
- Department of RadiologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Thomas H. Wassink
- Department of Psychiatry, Carver College of MedicineThe University of IowaIowa CityIowaUSA
| | - Bernd Weber
- Institute for Experimental Epileptology and Cognition ResearchUniversity of BonnBonnGermany
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of PsychiatryUniversity of New South WalesKensingtonNew South WalesAustralia
| | - John D. West
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | | | - Heather Whalley
- Division of PsychiatryUniversity of EdinburghEdinburghUnited Kingdom
| | - Lara M. Wierenga
- Developmental and Educational Psychology Unit, Institute of PsychologyLeiden UniversityLeidenNetherlands
| | - Katharina Wittfeld
- Department of Psychiatry and PsychotherapyUniversity Medicine Greifswald, University of GreifswaldGreifswaldGermany
- German Center for Neurodegenerative Diseases (DZNE)Site Rostock/GreifswaldGreifswaldGermany
| | - Daniel H. Wolf
- Department of PsychiatryUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Amanda Worker
- Department of Psychiatry, Djavad Mowafaghian Centre for Brain HealthUniversity of British ColumbiaVancouverCanada
| | | | - Kun Yang
- National High Magnetic Field LaboratoryFlorida State UniversityTallahasseeFloridaUSA
| | - Yulyia Yoncheva
- Department of Child and Adolescent Psychiatry, Child Study CenterNYU Langone HealthNew York CityNew YorkUSA
| | - Marcus V. Zanetti
- Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de MedicinaUniversidade de São PauloSão PauloBrazil
- Instituto de Ensino e PesquisaHospital Sírio‐LibanêsSão PauloBrazil
| | - Georg C. Ziegler
- Division of Molecular Psychiatry, Center of Mental HealthUniversity of WürzburgWürzburgGermany
| | | | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Danai Dima
- Department of NeuroimagingInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
- Department of Psychology, School of Arts and Social SciencesCity University of LondonLondonUnited Kingdom
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42
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Hosten N, Bülow R, Völzke H, Domin M, Schmidt CO, Teumer A, Ittermann T, Nauck M, Felix S, Dörr M, Markus MRP, Völker U, Daboul A, Schwahn C, Holtfreter B, Mundt T, Krey KF, Kindler S, Mksoud M, Samietz S, Biffar R, Hoffmann W, Kocher T, Chenot JF, Stahl A, Tost F, Friedrich N, Zylla S, Hannemann A, Lotze M, Kühn JP, Hegenscheid K, Rosenberg C, Wassilew G, Frenzel S, Wittfeld K, Grabe HJ, Kromrey ML. SHIP-MR and Radiology: 12 Years of Whole-Body Magnetic Resonance Imaging in a Single Center. Healthcare (Basel) 2021; 10:33. [PMID: 35052197 PMCID: PMC8775435 DOI: 10.3390/healthcare10010033] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 12/17/2021] [Accepted: 12/20/2021] [Indexed: 12/16/2022] Open
Abstract
The Study of Health in Pomerania (SHIP), a population-based study from a rural state in northeastern Germany with a relatively poor life expectancy, supplemented its comprehensive examination program in 2008 with whole-body MR imaging at 1.5 T (SHIP-MR). We reviewed more than 100 publications that used the SHIP-MR data and analyzed which sequences already produced fruitful scientific outputs and which manuscripts have been referenced frequently. Upon reviewing the publications about imaging sequences, those that used T1-weighted structured imaging of the brain and a gradient-echo sequence for R2* mapping obtained the highest scientific output; regarding specific body parts examined, most scientific publications focused on MR sequences involving the brain and the (upper) abdomen. We conclude that population-based MR imaging in cohort studies should define more precise goals when allocating imaging time. In addition, quality control measures might include recording the number and impact of published work, preferably on a bi-annual basis and starting 2 years after initiation of the study. Structured teaching courses may enhance the desired output in areas that appear underrepresented.
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Affiliation(s)
- Norbert Hosten
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany; (N.H.); (R.B.); (M.D.); (K.H.); (C.R.)
| | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany; (N.H.); (R.B.); (M.D.); (K.H.); (C.R.)
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany; (H.V.); (C.O.S.); (A.T.); (T.I.); (W.H.); (J.-F.C.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
| | - Martin Domin
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany; (N.H.); (R.B.); (M.D.); (K.H.); (C.R.)
| | - Carsten Oliver Schmidt
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany; (H.V.); (C.O.S.); (A.T.); (T.I.); (W.H.); (J.-F.C.)
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany; (H.V.); (C.O.S.); (A.T.); (T.I.); (W.H.); (J.-F.C.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
| | - Till Ittermann
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany; (H.V.); (C.O.S.); (A.T.); (T.I.); (W.H.); (J.-F.C.)
| | - Matthias Nauck
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Stephan Felix
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Department of Internal Medicine B, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Marcus Dörr
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Department of Internal Medicine B, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Marcello Ricardo Paulista Markus
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Department of Internal Medicine B, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Uwe Völker
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Interfaculty Institute of Genetics and Functional Genomics, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Amro Daboul
- Department of Prosthetic Dentistry, Gerodontology and Biomaterials, University Medicine Greifswald, 17475 Greifswald, Germany; (A.D.); (C.S.); (T.M.); (S.S.); (R.B.)
| | - Christian Schwahn
- Department of Prosthetic Dentistry, Gerodontology and Biomaterials, University Medicine Greifswald, 17475 Greifswald, Germany; (A.D.); (C.S.); (T.M.); (S.S.); (R.B.)
| | - Birte Holtfreter
- Department of Restorative Dentistry, Periodontology, Endodontology, and Preventive and Pediatric Dentistry, University Medicine Greifswald, 17475 Greifswald, Germany; (B.H.); (T.K.)
| | - Torsten Mundt
- Department of Prosthetic Dentistry, Gerodontology and Biomaterials, University Medicine Greifswald, 17475 Greifswald, Germany; (A.D.); (C.S.); (T.M.); (S.S.); (R.B.)
| | - Karl-Friedrich Krey
- Department of Orthodontics, University Medicine Greifswald, 17475 Greifswald, Germany;
| | - Stefan Kindler
- Department of Oral and Maxillofacial Surgery/Plastic Surgery, University Medicine Greifswald, 17475 Greifswald, Germany; (S.K.); (M.M.)
| | - Maria Mksoud
- Department of Oral and Maxillofacial Surgery/Plastic Surgery, University Medicine Greifswald, 17475 Greifswald, Germany; (S.K.); (M.M.)
| | - Stefanie Samietz
- Department of Prosthetic Dentistry, Gerodontology and Biomaterials, University Medicine Greifswald, 17475 Greifswald, Germany; (A.D.); (C.S.); (T.M.); (S.S.); (R.B.)
| | - Reiner Biffar
- Department of Prosthetic Dentistry, Gerodontology and Biomaterials, University Medicine Greifswald, 17475 Greifswald, Germany; (A.D.); (C.S.); (T.M.); (S.S.); (R.B.)
| | - Wolfgang Hoffmann
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany; (H.V.); (C.O.S.); (A.T.); (T.I.); (W.H.); (J.-F.C.)
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- German Centre for Neurodegenerative Diseases (DZNE), Partner Site Rostock/Greifswald, 17489 Greifswald, Germany
| | - Thomas Kocher
- Department of Restorative Dentistry, Periodontology, Endodontology, and Preventive and Pediatric Dentistry, University Medicine Greifswald, 17475 Greifswald, Germany; (B.H.); (T.K.)
| | - Jean-Francois Chenot
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany; (H.V.); (C.O.S.); (A.T.); (T.I.); (W.H.); (J.-F.C.)
| | - Andreas Stahl
- Clinic of Ophthalmology, University Medicine Greifswald, 17475 Greifswald, Germany; (A.S.); (F.T.)
| | - Frank Tost
- Clinic of Ophthalmology, University Medicine Greifswald, 17475 Greifswald, Germany; (A.S.); (F.T.)
| | - Nele Friedrich
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Stephanie Zylla
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Anke Hannemann
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, 10785 Berlin, Germany; (M.N.); (S.F.); (M.D.); (M.R.P.M.); (U.V.); (N.F.); (S.Z.); (A.H.)
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Martin Lotze
- Functional Imaging Unit, Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany;
| | - Jens-Peter Kühn
- Institute and Policlinic of Diagnostic and Interventional Radiology, Medical University, Carl-Gustav Carus, 01307 Dresden, Germany;
| | - Katrin Hegenscheid
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany; (N.H.); (R.B.); (M.D.); (K.H.); (C.R.)
| | - Christian Rosenberg
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany; (N.H.); (R.B.); (M.D.); (K.H.); (C.R.)
| | - Georgi Wassilew
- Clinic of Orthopedics, University Medicine Greifswald, 17475 Greifswald, Germany;
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany; (S.F.); (K.W.); (H.J.G.)
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany; (S.F.); (K.W.); (H.J.G.)
- German Center of Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Site Greifswald, 17489 Greifswald, Germany
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475 Greifswald, Germany; (S.F.); (K.W.); (H.J.G.)
- German Center of Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Site Greifswald, 17489 Greifswald, Germany
| | - Marie-Luise Kromrey
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17475 Greifswald, Germany; (N.H.); (R.B.); (M.D.); (K.H.); (C.R.)
- Correspondence:
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43
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Harrison LM, Noble DWA, Jennions MD. A meta-analysis of sex differences in animal personality: no evidence for the greater male variability hypothesis. Biol Rev Camb Philos Soc 2021; 97:679-707. [PMID: 34908228 DOI: 10.1111/brv.12818] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 11/13/2021] [Accepted: 11/17/2021] [Indexed: 12/18/2022]
Abstract
The notion that men are more variable than women has become embedded into scientific thinking. For mental traits like personality, greater male variability has been partly attributed to biology, underpinned by claims that there is generally greater variation among males than females in non-human animals due to stronger sexual selection on males. However, evidence for greater male variability is limited to morphological traits, and there is little information regarding sex differences in personality-like behaviours for non-human animals. Here, we meta-analysed sex differences in means and variances for over 2100 effects (204 studies) from 220 species (covering five broad taxonomic groups) across five personality traits: boldness, aggression, activity, sociality and exploration. We also tested if sexual size dimorphism, a proxy for sex-specific sexual selection, explains variation in the magnitude of sex differences in personality. We found no significant differences in personality between the sexes. In addition, sexual size dimorphism did not explain variation in the magnitude of the observed sex differences in the mean or variance in personality for any taxonomic group. In sum, we find no evidence for widespread sex differences in variability in non-human animal personality.
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Affiliation(s)
- Lauren M Harrison
- Division of Ecology and Evolution, Research School of Biology, The Australian National University, 46 Sullivans Creek Road, Canberra, ACT, 2600, Australia
| | - Daniel W A Noble
- Division of Ecology and Evolution, Research School of Biology, The Australian National University, 46 Sullivans Creek Road, Canberra, ACT, 2600, Australia
| | - Michael D Jennions
- Division of Ecology and Evolution, Research School of Biology, The Australian National University, 46 Sullivans Creek Road, Canberra, ACT, 2600, Australia
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44
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Thompson PM, Jahanshad N, Schmaal L, Turner JA, Winkler AM, Thomopoulos SI, Egan GF, Kochunov P. The Enhancing NeuroImaging Genetics through Meta-Analysis Consortium: 10 Years of Global Collaborations in Human Brain Mapping. Hum Brain Mapp 2021; 43:15-22. [PMID: 34612558 PMCID: PMC8675422 DOI: 10.1002/hbm.25672] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 09/09/2021] [Accepted: 09/16/2021] [Indexed: 12/23/2022] Open
Abstract
This Special Issue of Human Brain Mapping is dedicated to a 10-year anniversary of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium. It reports updates from a broad range of international neuroimaging projects that pool data from around the world to answer fundamental questions in neuroscience. Since ENIGMA was formed in December 2009, the initiative grew into a worldwide effort with over 2,000 participating scientists from 45 countries, and over 50 working groups leading large-scale studies of human brain disorders. Over the last decade, many lessons were learned on how best to pool brain data from diverse sources. Working groups were created to develop methods to analyze worldwide data from anatomical and diffusion magnetic resonance imaging (MRI), resting state and task-based functional MRI, electroencephalography (EEG), magnetoencephalography (MEG), and magnetic resonance spectroscopy (MRS). The quest to understand genetic effects on human brain development and disease also led to analyses of brain scans on an unprecedented scale. Genetic roadmaps of the human cortex were created by researchers worldwide who collaborated to perform statistically well-powered analyses of common and rare genetic variants on brain measures and rates of brain development and aging. Here, we summarize the 31 papers in this Special Issue, covering: (a) technical approaches to harmonize analysis of different types of brain imaging data, (b) reviews of the last decade of work by several of ENIGMA's clinical and technical working groups, and (c) new empirical papers reporting large-scale international brain mapping analyses in patients with substance use disorders, schizophrenia, bipolar disorders, major depression, posttraumatic stress disorder, obsessive compulsive disorder, epilepsy, and stroke.
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Affiliation(s)
- Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Lianne Schmaal
- Orygen, Parkville, Australia.,Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Jessica A Turner
- Psychology Department, Georgia State University, Atlanta, Georgia, USA
| | - Anderson M Winkler
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Bethesda, Maryland, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Gary F Egan
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia.,Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, Maryland, USA
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45
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Estimating the Additive Heritability of Historiometric Eminence in a Super-Pedigree Comprised of Four Prominent Families. Twin Res Hum Genet 2021; 24:191-199. [PMID: 34511158 DOI: 10.1017/thg.2021.29] [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: 11/06/2022]
Abstract
By merging analytical approaches from the fields of historiometrics and behavior genetics, a social pedigree-based estimate of the heritability of eminence is generated. Eminent individuals are identified using the Pantheon dataset. A single super-pedigree, comprised of four prominent and interrelated families (including the Wedgwood-Darwin, Arnold-Huxley, Keynes-Baha'u'lláh, and Benn-Rutherford pedigrees) is assembled, containing 30 eminent individuals out of 301 in total. Each eminent individual in the super-pedigree is assigned a relative measure of historical eminence (scaled from 1 to 100) with noneminent individuals assigned a score of 0. Utilizing a Bayesian pedigree-based heritability estimation procedure employing an informed prior, an additive heritability of eminence of .507 (95% CI [.434, .578]) was found. The finding that eminence is additively heritable is consistent with expectations from behavior-genetic studies of factors that are thought to underlie extraordinary accomplishment, which indicate that they are substantially additively heritable. Owing to the limited types of intermarriage present in the data, it was not possible to estimate the impact of nonadditive genetic contributions to heritability. Gene-by-environment interactions could not be estimated in the present analysis either; therefore, the finding that eminence is simply a function of additive genetic and nonshared environmental variance should be interpreted cautiously.
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46
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Williams CM, Peyre H, Toro R, Ramus F. Neuroanatomical norms in the UK Biobank: The impact of allometric scaling, sex, and age. Hum Brain Mapp 2021; 42:4623-4642. [PMID: 34268815 PMCID: PMC8410561 DOI: 10.1002/hbm.25572] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 06/03/2021] [Accepted: 06/11/2021] [Indexed: 12/18/2022] Open
Abstract
Few neuroimaging studies are sufficiently large to adequately describe population‐wide variations. This study's primary aim was to generate neuroanatomical norms and individual markers that consider age, sex, and brain size, from 629 cerebral measures in the UK Biobank (N = 40,028). The secondary aim was to examine the effects and interactions of sex, age, and brain allometry—the nonlinear scaling relationship between a region and brain size (e.g., total brain volume)—across cerebral measures. Allometry was a common property of brain volumes, thicknesses, and surface areas (83%) and was largely stable across age and sex. Sex differences occurred in 67% of cerebral measures (median |β| = .13): 37% of regions were larger in males and 30% in females. Brain measures (49%) generally decreased with age, although aging effects varied across regions and sexes. While models with an allometric or linear covariate adjustment for brain size yielded similar significant effects, omitting brain allometry influenced reported sex differences in variance. Finally, we contribute to the reproducibility of research on sex differences in the brain by replicating previous studies examining cerebral sex differences. This large‐scale study advances our understanding of age, sex, and brain allometry's impact on brain structure and provides data for future UK Biobank studies to identify the cerebral regions that covary with specific phenotypes, independently of sex, age, and brain size.
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Affiliation(s)
- Camille Michèle Williams
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France
| | - Hugo Peyre
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France.,INSERM UMR 1141, Paris Diderot University, Paris, France.,Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR 3571 CNRS, Paris, France.,Center for Research and Interdisciplinarity (CRI), INSERM U1284, Paris, France.,Université de Paris, Paris, France
| | - Franck Ramus
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France
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47
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Díaz-Caneja CM, Alloza C, Gordaliza PM, Fernández-Pena A, de Hoyos L, Santonja J, Buimer EEL, van Haren NEM, Cahn W, Arango C, Kahn RS, Hulshoff Pol HE, Schnack HG, Janssen J. Sex Differences in Lifespan Trajectories and Variability of Human Sulcal and Gyral Morphology. Cereb Cortex 2021; 31:5107-5120. [PMID: 34179960 DOI: 10.1093/cercor/bhab145] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 04/26/2021] [Accepted: 04/28/2021] [Indexed: 11/13/2022] Open
Abstract
Sex differences in the development and aging of human sulcal morphology have been understudied. We charted sex differences in trajectories and inter-individual variability of global sulcal depth, width, and length, pial surface area, exposed (hull) gyral surface area, unexposed sulcal surface area, cortical thickness, gyral span, and cortex volume across the lifespan in a longitudinal sample (700 scans, 194 participants 2 scans, 104 three scans, age range: 16-70 years) of neurotypical males and females. After adjusting for brain volume, females had thicker cortex and steeper thickness decline until age 40 years; trajectories converged thereafter. Across sexes, sulcal shortening was faster before age 40, while sulcal shallowing and widening were faster thereafter. Although hull area remained stable, sulcal surface area declined and was more strongly associated with sulcal shortening than with sulcal shallowing and widening. Males showed greater variability for cortex volume and lower variability for sulcal width. Our findings highlight the association between loss of sulcal area, notably through sulcal shortening, with cortex volume loss. Studying sex differences in lifespan trajectories may improve knowledge of individual differences in brain development and the pathophysiology of neuropsychiatric conditions.
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Affiliation(s)
- Covadonga M Díaz-Caneja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain.,Ciber del Área de Salud Mental (CIBERSAM), Avenida Monforte de Lemos, 3-5, Pabellón 11, 28029, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Calle Doctor Esquerdo, 46, 28007, Madrid, Spain.,Department of Legal Medicine, Psychiatry, and Pathology, School of Medicine, Universidad Complutense, Plaza Ramón y Cajal, s/n, Ciudad Universitaria, 28040, Madrid, Spain
| | - Clara Alloza
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain.,Ciber del Área de Salud Mental (CIBERSAM), Avenida Monforte de Lemos, 3-5, Pabellón 11, 28029, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Calle Doctor Esquerdo, 46, 28007, Madrid, Spain
| | - Pedro M Gordaliza
- Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Escuela Politécnica Superior, Avenida de la Universidad, 30, 28911, Leganés, Madrid, Spain
| | - Alberto Fernández-Pena
- Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Calle Doctor Esquerdo, 46, 28007, Madrid, Spain.,Departamento de Bioingeniería e Ingeniería Aeroespacial, Universidad Carlos III de Madrid, Escuela Politécnica Superior, Avenida de la Universidad, 30, 28911, Leganés, Madrid, Spain
| | - Lucía de Hoyos
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
| | - Javier Santonja
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain
| | - Elizabeth E L Buimer
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands
| | - Neeltje E M van Haren
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands.,Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre, Sophia Children's Hospital, Doctor Molewaterplein 40, 3015 GD, Rotterdam, the Netherlands
| | - Wiepke Cahn
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands
| | - Celso Arango
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain.,Ciber del Área de Salud Mental (CIBERSAM), Avenida Monforte de Lemos, 3-5, Pabellón 11, 28029, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Calle Doctor Esquerdo, 46, 28007, Madrid, Spain.,Department of Legal Medicine, Psychiatry, and Pathology, School of Medicine, Universidad Complutense, Plaza Ramón y Cajal, s/n, Ciudad Universitaria, 28040, Madrid, Spain
| | - René S Kahn
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY 10029, USA
| | - Hilleke E Hulshoff Pol
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands
| | - Hugo G Schnack
- Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands
| | - Joost Janssen
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Calle Ibiza, 43, 28009, Madrid, Spain.,Ciber del Área de Salud Mental (CIBERSAM), Avenida Monforte de Lemos, 3-5, Pabellón 11, 28029, Madrid, Spain.,Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Calle Doctor Esquerdo, 46, 28007, Madrid, Spain.,Department of Psychiatry, UMCU Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands
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48
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Norbom LB, Ferschmann L, Parker N, Agartz I, Andreassen OA, Paus T, Westlye LT, Tamnes CK. New insights into the dynamic development of the cerebral cortex in childhood and adolescence: Integrating macro- and microstructural MRI findings. Prog Neurobiol 2021; 204:102109. [PMID: 34147583 DOI: 10.1016/j.pneurobio.2021.102109] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 04/26/2021] [Accepted: 06/15/2021] [Indexed: 12/11/2022]
Abstract
Through dynamic transactional processes between genetic and environmental factors, childhood and adolescence involve reorganization and optimization of the cerebral cortex. The cortex and its development plays a crucial role for prototypical human cognitive abilities. At the same time, many common mental disorders appear during these critical phases of neurodevelopment. Magnetic resonance imaging (MRI) can indirectly capture several multifaceted changes of cortical macro- and microstructure, of high relevance to further our understanding of the neural foundation of cognition and mental health. Great progress has been made recently in mapping the typical development of cortical morphology. Moreover, newer less explored MRI signal intensity and specialized quantitative T2 measures have been applied to assess microstructural cortical development. We review recent findings of typical postnatal macro- and microstructural development of the cerebral cortex from early childhood to young adulthood. We cover studies of cortical volume, thickness, area, gyrification, T1-weighted (T1w) tissue contrasts such a grey/white matter contrast, T1w/T2w ratio, magnetization transfer and myelin water fraction. Finally, we integrate imaging studies with cortical gene expression findings to further our understanding of the underlying neurobiology of the developmental changes, bridging the gap between ex vivo histological- and in vivo MRI studies.
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Affiliation(s)
- Linn B Norbom
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
| | - Lia Ferschmann
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway
| | - Nadine Parker
- Institute of Medical Science, University of Toronto, Ontario, Canada
| | - Ingrid Agartz
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway
| | - Ole A Andreassen
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway
| | - Tomáš Paus
- ECOGENE-21, Chicoutimi, Quebec, Canada; Department of Psychology and Psychiatry, University of Toronto, Ontario, Canada; Department of Psychiatry and Centre hospitalier universitaire Sainte-Justine, University of Montreal, Canada
| | - Lars T Westlye
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychology, University of Oslo, Norway
| | - Christian K Tamnes
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway.
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49
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Converging evidence for greater male variability in time, risk, and social preferences. Proc Natl Acad Sci U S A 2021; 118:2026112118. [PMID: 34088838 DOI: 10.1073/pnas.2026112118] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Gender differences in time, risk, and social preferences are important determinants of differential choices of men and women, with broad implications for gender-specific social and economic outcomes. To better understand the shape and form of gender differences in preferences, researchers have traditionally examined the mean differences between the two genders. We present an alternative perspective of greater male variability in preferences. In a meta-analysis of experimental economics studies with more than 50,000 individuals in 97 samples, we find converging evidence for greater male variability in time, risk, and social preferences. In some cases, we find greater male variability in addition to mean differences; in some cases, we only find greater male variability. Our findings suggest that theories of gender differences are incomplete if they fail to consider how the complex interaction of between-gender differences and within-gender variability determines differential choices and outcomes between women and men.
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50
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Podgórski P, Bladowska J, Sasiadek M, Zimny A. Novel Volumetric and Surface-Based Magnetic Resonance Indices of the Aging Brain - Does Male and Female Brain Age in the Same Way? Front Neurol 2021; 12:645729. [PMID: 34163419 PMCID: PMC8216769 DOI: 10.3389/fneur.2021.645729] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 04/20/2021] [Indexed: 12/21/2022] Open
Abstract
Introduction: Novel post-processing methods allow not only for assessment of brain volumetry or cortical thickness based on magnetic resonance imaging (MRI) but also for more detailed analysis of cortical shape and complexity using parameters such as sulcal depth, gyrification index, or fractal dimension. The aim of this study was to analyze changes in brain volumetry and other cortical indices during aging in men and women. Material and Methods: Material consisted of 697 healthy volunteers (aged 38–80 years; M/F, 264/443) who underwent brain MRI using a 1.5-T scanner. Voxel-based volumetry of total gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) was performed followed by assessment of cortical parameters [cortical thickness (CT), sulcal depth (SD), gyrification index (GI), and fractal dimension (FD)] in 150 atlas locations using surface-based morphometry with a region-based approach. All parameters were compared among seven age groups (grouped every 5 years) separately for men and women. Additionally, percentile curves for men and women were provided for total volumes of GM, WM, and CSF. Results: In men and women, a decrease in GM and WM volumes and an increase in CSF volume seem to progress slowly since the age of 45. In men, significant GM and WM loss as well as CSF increase start above 55 years of age, while in women, significant GM loss starts above 50 and significant WM loss as well as CSF increase above 60. CT was found to significantly decrease with aging in 39% of locations in women and in 36% of locations in men, SD was found to increase in 13.5% of locations in women and in 1.3% of locations in men, GI was decreased in 3.4% of locations in women and in 2.0% of locations in men, and FD was changed in 2.7% of locations in women compared to 2.0% in men. Conclusions: Male and female brains start aging at the similar age of 45. Compared to men, in women, the cortex is affected earlier and in the more complex pattern regarding not only cortical loss but also other alterations within the cortical shape, with relatively longer sparing of WM volume.
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Affiliation(s)
- Przemysław Podgórski
- Department of General and Interventional Radiology and Neuroradiology, Wroclaw Medical University, Wrocław, Poland
| | - Joanna Bladowska
- Department of General and Interventional Radiology and Neuroradiology, Wroclaw Medical University, Wrocław, Poland
| | - Marek Sasiadek
- Department of General and Interventional Radiology and Neuroradiology, Wroclaw Medical University, Wrocław, Poland
| | - Anna Zimny
- Department of General and Interventional Radiology and Neuroradiology, Wroclaw Medical University, Wrocław, Poland
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