1
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Taskin HO, Qiao Y, Sydnor VJ, Cieslak M, Haggerty EB, Satterthwaite TD, Morgan JI, Shi Y, Aguirre GK. Retinal ganglion cell endowment is correlated with optic tract fiber cross section, not density. Neuroimage 2022; 260:119495. [PMID: 35868617 PMCID: PMC10362491 DOI: 10.1016/j.neuroimage.2022.119495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 06/27/2022] [Accepted: 07/19/2022] [Indexed: 11/30/2022] Open
Abstract
There is substantial variation between healthy individuals in the number of retinal ganglion cells (RGC) in the eye, with commensurate variation in the number of axons in the optic tracts. Fixel-based analysis of diffusion MR produces estimates of fiber density (FD) and cross section (FC). Using these fixel measurements along with retinal imaging, we asked if individual differences in RGC tissue volume are correlated with individual differences in FD and FC measurements obtained from the optic tracts, and subsequent structures along the cortical visual pathway. We find that RGC endowment is correlated with optic tract FC, but not with FD. RGC volume had a decreasing relationship with measurements from subsequent regions of the visual system (LGN volume, optic radiation FC/FD, and V1 surface area). However, we also found that the variations in each visual area were correlated with the variations in its immediately adjacent visual structure. We only observed these serial correlations when FC is used as the measure of interest for the optic tract and radiations, but no significant relationship was found when FD represented these white matter structures. From these results, we conclude that the variations in RGC endowment, LGN volume, and V1 surface area are better predicted by the overall cross section of the optic tract and optic radiations as compared to the intra-axonal restricted signal component of these white matter pathways. Additionally, the presence of significant correlations between adjacent, but not distant, anatomical structures suggests that there are multiple, local sources of anatomical variation along the visual pathway.
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Affiliation(s)
- Huseyin O Taskin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Yuchuan Qiao
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033
| | - Valerie J Sydnor
- Biomedical Graduate Studies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Matthew Cieslak
- Department of Neuropsychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Edda B Haggerty
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Theodore D Satterthwaite
- Department of Psychiatry, Penn Lifespan Informatics and Neuroimaging Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Jessica Iw Morgan
- Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Yonggang Shi
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033
| | - Geoffrey K Aguirre
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104.
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2
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Norbom LB, Hanson J, van der Meer D, Ferschmann L, Røysamb E, von Soest T, Andreassen OA, Agartz I, Westlye LT, Tamnes CK. Parental socioeconomic status is linked to cortical microstructure and language abilities in children and adolescents. Dev Cogn Neurosci 2022; 56:101132. [PMID: 35816931 PMCID: PMC9284438 DOI: 10.1016/j.dcn.2022.101132] [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: 01/31/2022] [Revised: 05/11/2022] [Accepted: 06/30/2022] [Indexed: 12/17/2022] Open
Abstract
Gradients in parental socioeconomic status (SES) are closely linked to important life outcomes in children and adolescents, such as cognitive abilities, school achievement, and mental health. Parental SES may also influence brain development, with several magnetic resonance imaging (MRI) studies reporting associations with youth brain morphometry. However, MRI signal intensity metrics have not been assessed, but could offer a microstructural correlate, thereby increasing our understanding of SES influences on neurobiology. We computed a parental SES score from family income, parental education and parental occupation, and assessed relations with cortical microstructure as measured by T1w/T2w ratio (n = 504, age = 3-21 years). We found negative age-stabile relations between parental SES and T1w/T2w ratio, indicating that youths from lower SES families have higher ratio in widespread frontal, temporal, medial parietal and occipital regions, possibly indicating a more developed cortex. Effect sizes were small, but larger than for conventional morphometric properties i.e. cortical surface area and thickness, which were not significantly associated with parental SES. Youths from lower SES families had poorer language related abilities, but microstructural differences did not mediate these relations. T1w/T2w ratio appears to be a sensitive imaging marker for further exploring the association between parental SES and child brain development.
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Affiliation(s)
- Linn B. Norbom
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway,NORMENT, Institute of Clinical Medicine, University of Oslo, Norway,Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway,Norwegian Institute of Public Health, Norway,Correspondence to: P.O. box 1094 Blindern, 0317 Oslo, Norway.
| | - Jamie Hanson
- Learning Research and Development Center University of Pittsburgh, USA,Department of Psychology, University of Pittsburgh, USA,Norwegian Institute of Public Health, Norway
| | - Dennis van der Meer
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway,School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands,Norwegian Institute of Public Health, Norway
| | - Lia Ferschmann
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway,Norwegian Institute of Public Health, Norway
| | - Espen Røysamb
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway,Department of Psychology, University of Oslo, Norway,Norwegian Institute of Public Health, Norway
| | - Tilmann von Soest
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway,Norwegian Institute of Public Health, 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,Norwegian Institute of Public Health, Norway
| | - 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,Norwegian Institute of Public Health, Norway,Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - 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,Norwegian Institute of Public Health, Norway
| | - Christian K. Tamnes
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway,NORMENT, Institute of Clinical Medicine, University of Oslo, Norway,Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway,Norwegian Institute of Public Health, Norway
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3
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Hu Y, Tan H, Li C, Zhang H. Identifying genetic risk variants associated with brain volumetric phenotypes via K-sample Ball Divergence method. Genet Epidemiol 2021; 45:710-720. [PMID: 34184773 PMCID: PMC8434958 DOI: 10.1002/gepi.22423] [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: 09/30/2020] [Revised: 06/07/2021] [Accepted: 06/17/2021] [Indexed: 02/05/2023]
Abstract
Regional human brain volumes including total area, average thickness, and total volume are heritable and associated with neurological disorders. However, the genetic architecture of brain structure and function is still largely unknown and worthy of exploring. The Pediatric Imaging, Neurocognition, and Genetics (PING) data set provides an excellent resource with genome-wide genetic data and related neuroimaging data. In this study, we perform genome-wide association studies (GWAS) of 315 brain volumetric phenotypes from the PING data set including 1036 samples with 539,865 single-nucleotide polymorphisms (SNPs). We introduce a nonparametric test based on K-sample Ball Divergence (KBD) to identify genetic risk variants that influence regional brain volumes. We carry out simulations to demonstrate that KBD is a powerful test for identifying significant SNPs associated with multivariate phenotypes although controlling the type I error rate. We successfully identify nine SNPs below a significance level of 5 × 10-5 for the PING data. Among the nine identified genetic variants, two SNPs rs486179 and rs562110 are located in the ADRA1A gene that is a well-known risk factor of mental illness, such as schizophrenia and attention deficit hyperactivity disorder. Our study suggests that the nonparametric test KBD is an effective method for identifying genetic variants associated with complex diseases in large-scale GWAS of multiple phenotypes.
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Affiliation(s)
- Yue Hu
- Department of Biostatistics, Yale University School of Public Health, New Haven, CT, 06511
| | - Haizhu Tan
- Department of Preventive Medicine, Shantou University Medical College, Xinling Road 22, Shantou, Guangdong, P. R. China
| | - Cai Li
- Department of Biostatistics, Yale University School of Public Health, New Haven, CT, 06511
| | - Heping Zhang
- Department of Biostatistics, Yale University School of Public Health, New Haven, CT, 06511
- Correspondence Author: Heping Zhang, 300 George Street, Ste 523, New Haven, CT, 06511. . Phone: 203-785-5185
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4
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Bystritsky A, Spivak NM, Dang BH, Becerra SA, Distler MG, Jordan SE, Kuhn TP. Brain circuitry underlying the ABC model of anxiety. J Psychiatr Res 2021; 138:3-14. [PMID: 33798786 DOI: 10.1016/j.jpsychires.2021.03.030] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 03/12/2021] [Accepted: 03/17/2021] [Indexed: 12/13/2022]
Abstract
Anxiety Disorders are prevalent and often chronic, recurrent conditions that reduce quality of life. The first-line treatments, such as serotonin reuptake inhibitors and cognitive behavioral therapy, leave a significant proportion of patients symptomatic. As psychiatry moves toward targeted circuit-based treatments, there is a need for a theory that unites the phenomenology of anxiety with its underlying neural circuits. The Alarm, Belief, Coping (ABC) theory of anxiety describes how the neural circuits associated with anxiety interact with each other and domains of the anxiety symptoms, both temporally and spatially. The latest advancements in neuroimaging techniques offer the ability to assess these circuits in vivo. Using Neurosynth, a large open-access meta-analytic imaging database, the association between terms related to specific neural circuits was explored within the ABC theory framework. Alarm-related terms were associated with the amygdala, anterior cingulum, insula, and bed nucleus of stria terminalis. Belief-related terms were associated with medial prefrontal cortex, precuneus, bilateral temporal poles, and hippocampus. Coping-related terms were associated with the ventrolateral and dorsolateral prefrontal cortices, basal ganglia, and anterior cingulate. Neural connections underlying the functional neuroanatomy of the ABC model were observed. Additionally, there was considerable interaction and overlap between circuits associated with the symptom domains. Further neuroimaging research is needed to explore the dynamic interaction between the functional domains of the ABC theory. This will pave the way for probing the neuroanatomical underpinnings of anxiety disorders and provide an evidence-based foundation for the development of targeted treatments, such as neuromodulation.
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Affiliation(s)
- Alexander Bystritsky
- Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles, CA, USA; BrainSonix Corporation, Sherman Oaks, CA, USA.
| | - Norman M Spivak
- Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles, CA, USA; Department of Neurosurgery, UCLA, Los Angeles, CA, USA; David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Bianca H Dang
- Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles, CA, USA
| | - Sergio A Becerra
- Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles, CA, USA
| | - Margaret G Distler
- Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles, CA, USA
| | - Sheldon E Jordan
- Neurology Management Associates - Los Angeles, Santa Monica, CA, USA
| | - Taylor P Kuhn
- Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles, CA, USA; David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
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5
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Assessing speech exposure in the NICU: Implications for speech enrichment for preterm infants. J Perinatol 2020; 40:1537-1545. [PMID: 32362660 PMCID: PMC8189318 DOI: 10.1038/s41372-020-0672-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 03/17/2020] [Accepted: 04/20/2020] [Indexed: 11/20/2022]
Abstract
OBJECTIVE Quantify NICU speech exposure over multiple days in relation to NICU care practices. METHODS Continuous measures of speech exposure were obtained for preterm infants (n = 21; 12 M) born <34 weeks gestational age in incubators (n = 12) or open cribs (n = 9) for 5-14 days. Periods of care (routine, developmental) and delivery source (family, medical staff, cuddler) were determined through chart review. RESULTS Infants spent 13% of their time in Care, with >75% of care time reflecting developmental care. Speech counts were higher during care than no care, for mature vs. immature infants, and for infants in open cribs vs. incubators. Family participation in care ranged widely, with the highest speech counts occurring during periods of intentional voice exposure. CONCLUSIONS Care activities represent a small portion of NICU experiences. Speech exposure during Developmental Care, especially with intentional voice exposure, may be an important source of stimulation. Implications for care practices are discussed.
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6
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Di Plinio S, Ebisch SJH. Combining local and global evolutionary trajectories of brain-behaviour relationships through game theory. Eur J Neurosci 2020; 52:4198-4213. [PMID: 32594640 DOI: 10.1111/ejn.14883] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 06/15/2020] [Accepted: 06/20/2020] [Indexed: 01/05/2023]
Abstract
The study of the evolution of brain-behaviour relationships concerns understanding the causes and repercussions of cross- and within-species variability. Understanding such variability is a main objective of evolutionary and cognitive neuroscience, and it may help explaining the appearance of psychopathological phenotypes. Although brain evolution is related to the progressive action of selection and adaptation through multiple paths (e.g. mosaic vs. concerted evolution, metabolic vs. structural and functional constraints), a coherent, integrative framework is needed to combine evolutionary paths and neuroscientific evidence. Here, we review the literature on evolutionary pressures focusing on structural-functional changes and developmental constraints. Taking advantage of recent progress in neuroimaging and cognitive neuroscience, we propose a twofold hypothetical model of brain evolution. Within this model, global and local trajectories imply rearrangements of neural subunits and subsystems and of behavioural repertoires of a species, respectively. We incorporate these two processes in a game in which the global trajectory shapes the structural-functional neural substrates (i.e. players), while the local trajectory shapes the behavioural repertoires (i.e. stochastic payoffs).
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Affiliation(s)
- Simone Di Plinio
- Department of Neuroscience, Imaging, and Clinical Sciences, G D'Annunzio University of Chieti-Pescara, Chieti, Italy
| | - Sjoerd J H Ebisch
- Department of Neuroscience, Imaging, and Clinical Sciences, G D'Annunzio University of Chieti-Pescara, Chieti, Italy.,Institute for Advanced Biomedical Technologies (ITAB), G D'Annunzio University of Chieti Pescara, Chieti, Italy
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7
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Strike LT, Hansell NK, Couvy-Duchesne B, Thompson PM, de Zubicaray GI, McMahon KL, Wright MJ. Genetic Complexity of Cortical Structure: Differences in Genetic and Environmental Factors Influencing Cortical Surface Area and Thickness. Cereb Cortex 2020; 29:952-962. [PMID: 29377989 DOI: 10.1093/cercor/bhy002] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2017] [Indexed: 12/15/2022] Open
Abstract
Quantifying the genetic architecture of the cerebral cortex is necessary for understanding disease and changes to the brain across the lifespan. Prior work shows that both surface area (SA) and cortical thickness (CT) are heritable. However, we do not yet understand the extent to which region-specific genetic factors (i.e., independent of global effects) play a dominant role in the regional patterning or inter-regional associations across the cortex. Using a population sample of young adult twins (N = 923), we show that the heritability of SA and CT varies widely across regions, generally independent of measurement error. When global effects are controlled for, we detected a complex pattern of genetically mediated clusters of inter-regional associations, which varied between hemispheres. There were generally weak associations between the SA of different regions, except within the occipital lobe, whereas CT was positively correlated within lobar divisions and negatively correlated across lobes, mostly due to genetic covariation. These findings were replicated in an independent sample of twins and siblings (N = 698) from the Human Connectome Project. The different genetic contributions to SA and CT across regions reveal the value of quantifying sources of covariation to appreciate the genetic complexity of cortical structures.
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Affiliation(s)
- Lachlan T Strike
- Queensland Brain Institute, University of Queensland, Brisbane QLD, Australia
| | - Narelle K Hansell
- Queensland Brain Institute, University of Queensland, Brisbane QLD, Australia
| | | | - Paul M Thompson
- Imaging Genetics Center, University of Southern California, Marina del Rey, CA, USA
| | - Greig I de Zubicaray
- Faculty of Health and Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane QLD, Australia
| | - Katie L McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane QLD, Australia
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane QLD, Australia.,Centre for Advanced Imaging, University of Queensland, Brisbane QLD, Australia
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8
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Xu JZ, Kumar R, Gong H, Liu L, Ramos-Solis N, Li Y, Derbigny WA. Toll-Like Receptor 3 Deficiency Leads to Altered Immune Responses to Chlamydia trachomatis Infection in Human Oviduct Epithelial Cells. Infect Immun 2019; 87:e00483-19. [PMID: 31383744 PMCID: PMC6759307 DOI: 10.1128/iai.00483-19] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2019] [Accepted: 07/26/2019] [Indexed: 12/16/2022] Open
Abstract
Reproductive tract pathology caused by Chlamydia trachomatis infection is an important global cause of human infertility. To better understand the mechanisms associated with Chlamydia-induced genital tract pathogenesis in humans, we used CRISPR genome editing to disrupt Toll-like receptor 3 (TLR3) function in the human oviduct epithelial (hOE) cell line OE-E6/E7 in order to investigate the possible role(s) of TLR3 signaling in the immune response to Chlamydia Disruption of TLR3 function in these cells significantly diminished the Chlamydia-induced synthesis of several inflammation biomarkers, including interferon beta (IFN-β), interleukin-6 (IL-6), interleukin-6 receptor alpha (IL-6Rα), soluble interleukin-6 receptor beta (sIL-6Rβ, or gp130), IL-8, IL-20, IL-26, IL-34, soluble tumor necrosis factor receptor 1 (sTNF-R1), tumor necrosis factor ligand superfamily member 13B (TNFSF13B), matrix metalloproteinase 1 (MMP-1), MMP-2, and MMP-3. In contrast, the Chlamydia-induced synthesis of CCL5, IL-29 (IFN-λ1), and IL-28A (IFN-λ2) was significantly increased in TLR3-deficient hOE cells compared to their wild-type counterparts. Our results indicate a role for TLR3 signaling in limiting the genital tract fibrosis, scarring, and chronic inflammation often associated with human chlamydial disease. Interestingly, we saw that Chlamydia infection induced the production of biomarkers associated with persistence, tumor metastasis, and autoimmunity, such as soluble CD163 (sCD163), chitinase-3-like protein 1, osteopontin, and pentraxin-3, in hOE cells; however, their expression levels were significantly dysregulated in TLR3-deficient hOE cells. Finally, we demonstrate using hOE cells that TLR3 deficiency resulted in an increased amount of chlamydial lipopolysaccharide (LPS) within Chlamydia inclusions, which is suggestive that TLR3 deficiency leads to enhanced chlamydial replication and possibly increased genital tract pathogenesis during human infection.
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Affiliation(s)
- Jerry Z Xu
- Department of Microbiology and Immunology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ramesh Kumar
- Department of Microbiology and Immunology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Haoli Gong
- Xiangya Second Hospital, Central South University, Changsha, Hunan Province, People's Republic of China
| | - Luyao Liu
- Xiangya Second Hospital, Central South University, Changsha, Hunan Province, People's Republic of China
| | - Nicole Ramos-Solis
- Department of Microbiology and Immunology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Yujing Li
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Wilbert A Derbigny
- Department of Microbiology and Immunology, Indiana University School of Medicine, Indianapolis, Indiana, USA
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9
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Pearson J. The human imagination: the cognitive neuroscience of visual mental imagery. Nat Rev Neurosci 2019; 20:624-634. [DOI: 10.1038/s41583-019-0202-9] [Citation(s) in RCA: 181] [Impact Index Per Article: 36.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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10
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Ong ML, Tuan TA, Poh J, Teh AL, Chen L, Pan H, MacIsaac JL, Kobor MS, Chong YS, Kwek K, Saw SM, Godfrey KM, Gluckman PD, Fortier MV, Karnani N, Meaney MJ, Qiu A, Holbrook JD. Neonatal amygdalae and hippocampi are influenced by genotype and prenatal environment, and reflected in the neonatal DNA methylome. GENES BRAIN AND BEHAVIOR 2019; 18:e12576. [PMID: 31020763 DOI: 10.1111/gbb.12576] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 03/01/2019] [Accepted: 04/13/2019] [Indexed: 12/28/2022]
Abstract
The amygdala and hippocampus undergo rapid development in early life. The relative contribution of genetic and environmental factors to the establishment of their developmental trajectories has yet to be examined. We performed imaging on neonates and examined how the observed variation in volume and microstructure of the amygdala and hippocampus varied by genotype, and compared with prenatal maternal mental health and socioeconomic status. Gene × Environment models outcompeted models containing genotype or environment only to best explain the majority of measures but some, especially of the amygdaloid microstructure, were best explained by genotype only. Models including DNA methylation measured in the neonate umbilical cords outcompeted the Gene and Gene × Environment models for the majority of amygdaloid measures and minority of hippocampal measures. This study identified brain region-specific gene networks associated with individual differences in fetal brain development. In particular, genetic and epigenetic variation within CUX1 was highlighted.
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Affiliation(s)
- Mei-Lyn Ong
- Singapore Institute of Clinical sciences (SICS), A*STAR, Brenner Centre for Molecular Medicine, Singapore
| | - Ta A Tuan
- Department of Biomedical Engineering, Clinical Imaging research Centre, National University of Singapore, Singapore
| | - Joann Poh
- Department of Biomedical Engineering, Clinical Imaging research Centre, National University of Singapore, Singapore
| | - Ai L Teh
- Singapore Institute of Clinical sciences (SICS), A*STAR, Brenner Centre for Molecular Medicine, Singapore
| | - Li Chen
- Singapore Institute of Clinical sciences (SICS), A*STAR, Brenner Centre for Molecular Medicine, Singapore
| | - Hong Pan
- Singapore Institute of Clinical sciences (SICS), A*STAR, Brenner Centre for Molecular Medicine, Singapore.,School of Computer Engineering, Nanyang Technological University (NTU), Singapore
| | - Julia L MacIsaac
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Michael S Kobor
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Yap S Chong
- Singapore Institute of Clinical sciences (SICS), A*STAR, Brenner Centre for Molecular Medicine, Singapore.,Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore
| | - Kenneth Kwek
- KK Women's and Children's Hospital, Duke National University of Singapore, Singapore
| | - Seang M Saw
- Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore
| | - Keith M Godfrey
- MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Peter D Gluckman
- Singapore Institute of Clinical sciences (SICS), A*STAR, Brenner Centre for Molecular Medicine, Singapore.,Centre for Human Evolution, Adaptation and disease, Liggins Institute, University of Auckland, Auckland, New Zealand
| | - Marielle V Fortier
- KK Women's and Children's Hospital, Duke National University of Singapore, Singapore
| | - Neerja Karnani
- Singapore Institute of Clinical sciences (SICS), A*STAR, Brenner Centre for Molecular Medicine, Singapore
| | - Michael J Meaney
- Singapore Institute of Clinical sciences (SICS), A*STAR, Brenner Centre for Molecular Medicine, Singapore.,Ludmer Centre for Neuroinformatics and Mental Health, Sackler Program for Epigenetics & Psychobiology at McGill University, Douglas University Mental Health Institute, McGill University, Montreal, Canada
| | - Anqi Qiu
- Department of Biomedical Engineering, Clinical Imaging research Centre, National University of Singapore, Singapore.,Singapore Institute of Clinical sciences (SICS), A*STAR, Brenner Centre for Molecular Medicine, Singapore
| | - Joanna D Holbrook
- Singapore Institute of Clinical sciences (SICS), A*STAR, Brenner Centre for Molecular Medicine, Singapore
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11
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Piccolo LR, Merz EC, Noble KG. School climate is associated with cortical thickness and executive function in children and adolescents. Dev Sci 2019; 22:e12719. [PMID: 30156357 PMCID: PMC6294656 DOI: 10.1111/desc.12719] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2017] [Accepted: 07/02/2018] [Indexed: 01/19/2023]
Abstract
A positive school climate has been found to support mental and physical health, academic achievement and social adjustment among youth. However, links between school climate and brain structure have not been investigated to date. In this study, we investigated whether school climate was associated with executive function (EF) and brain structure (cortical thickness and surface area) in children and adolescents. We further examined whether these links varied as a function of socioeconomic background. Participants who ranged from 9 to 18 years of age (N = 108) completed EF tasks and a high-resolution, 3-Tesla, T1-weighted magnetic resonance imaging (MRI) scan. Overall school climate, academic support, and family socioeconomic background were assessed using questionnaires. Higher academic support was associated with greater EF task performance and increased global cortical thickness. Additionally, academic support moderated the association between family income and EF, such that children from lower income families performed similarly to their more advantaged peers on EF tasks in the context of positive academic support. This work is the first to link school climate to brain structure and contributes to the growing body of evidence suggesting that academic support may be an important protective factor in the context of socioeconomic disadvantage.
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Affiliation(s)
- Luciane R. Piccolo
- Department of Biobehavioral Sciences, Teachers College, Columbia University, New York, NY, 10027
| | - Emily C. Merz
- Department of Biobehavioral Sciences, Teachers College, Columbia University, New York, NY, 10027
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12
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Reardon PK, Seidlitz J, Vandekar S, Liu S, Patel R, Park MTM, Alexander-Bloch A, Clasen LS, Blumenthal JD, Lalonde FM, Giedd JN, Gur RC, Gur RE, Lerch JP, Chakravarty MM, Satterthwaite TD, Shinohara RT, Raznahan A. Normative brain size variation and brain shape diversity in humans. Science 2018; 360:1222-1227. [PMID: 29853553 PMCID: PMC7485526 DOI: 10.1126/science.aar2578] [Citation(s) in RCA: 117] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 04/09/2018] [Indexed: 01/09/2023]
Abstract
Brain size variation over primate evolution and human development is associated with shifts in the proportions of different brain regions. Individual brain size can vary almost twofold among typically developing humans, but the consequences of this for brain organization remain poorly understood. Using in vivo neuroimaging data from more than 3000 individuals, we find that larger human brains show greater areal expansion in distributed frontoparietal cortical networks and related subcortical regions than in limbic, sensory, and motor systems. This areal redistribution recapitulates cortical remodeling across evolution, manifests by early childhood in humans, and is linked to multiple markers of heightened metabolic cost and neuronal connectivity. Thus, human brain shape is systematically coupled to naturally occurring variations in brain size through a scaling map that integrates spatiotemporally diverse aspects of neurobiology.
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Affiliation(s)
- P K Reardon
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA
- Department of Physiology, Anatomy and Genetics, Oxford University, UK
- Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Jakob Seidlitz
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA
- Department of Psychiatry, Cambridge University, Cambridge, UK
| | - Simon Vandekar
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Siyuan Liu
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Raihaan Patel
- Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Min Tae M Park
- Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | | | - Liv S Clasen
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Jonathan D Blumenthal
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Francois M Lalonde
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Jay N Giedd
- Department of Psychiatry, University of California-San Diego, La Jolla, CA, USA
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jason P Lerch
- Mouse Imaging Center, Hospital for Sick Children, Toronto, ON, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | | | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Armin Raznahan
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA.
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13
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Mollon JD, Bosten JM, Peterzell DH, Webster MA. Individual differences in visual science: What can be learned and what is good experimental practice? Vision Res 2017; 141:4-15. [PMID: 29129731 PMCID: PMC5730466 DOI: 10.1016/j.visres.2017.11.001] [Citation(s) in RCA: 70] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2017] [Revised: 11/07/2017] [Accepted: 11/08/2017] [Indexed: 01/21/2023]
Abstract
We all pass out our lives in private perceptual worlds. The differences in our sensory and perceptual experiences often go unnoticed until there emerges a variation (such as 'The Dress') that is large enough to generate different descriptions in the coarse coinage of our shared language. In this essay, we illustrate how individual differences contribute to a richer understanding of visual perception, but we also indicate some potential pitfalls that face the investigator who ventures into the field.
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Affiliation(s)
- John D Mollon
- Department of Psychology, University of Cambridge, United Kingdom
| | - Jenny M Bosten
- School of Psychology, University of Sussex, United Kingdom
| | | | - Michael A Webster
- Department of Psychology and Graduate Program in Integrative Neuroscience, University of Nevada, Reno, United States.
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14
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Piccolo LR, Noble KG. Perceived stress is associated with smaller hippocampal volume in adolescence. Psychophysiology 2017; 55:e13025. [PMID: 29053191 DOI: 10.1111/psyp.13025] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Revised: 09/15/2017] [Accepted: 09/22/2017] [Indexed: 12/11/2022]
Abstract
Perceived stress has been associated with decreased hippocampal, amygdala, and prefrontal cortex volume, as well as decreased memory and executive functioning performance in adulthood. Parents' perceived stress has been linked to decreased hippocampal volume in young children. However, no studies have investigated the links between self-perceived stress and brain structure or function in adolescents. Additionally, findings from previous research with younger or older samples are inconsistent, likely in part due to inconsistencies in participants' age range. In this study, we investigated the associations among self-perceived stress, family socioeconomic factors (family income, parental education), subcortical (hippocampus, amygdala) volumes, prefrontal cortical thickness and surface area, and memory and executive functioning performance in adolescents. One hundred and forty-three participants (12-20 years old) were administered a cognitive battery, a questionnaire to assess perceived stress, and a structural MRI scan. Higher levels of perceived stress were associated with decreased adolescent hippocampal volume. This study provides empirical evidence of how experience may shape brain development in adolescence-a period of plasticity during which it may be possible to intervene and prevent negative developmental outcomes.
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15
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Merz EC, Tottenham N, Noble KG. Socioeconomic Status, Amygdala Volume, and Internalizing Symptoms in Children and Adolescents. JOURNAL OF CLINICAL CHILD AND ADOLESCENT PSYCHOLOGY 2017; 47:312-323. [PMID: 28574722 DOI: 10.1080/15374416.2017.1326122] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
The associations among socioeconomic disadvantage, amygdala volume, and internalizing symptoms in children and adolescents are unclear and understudied in the extant literature. In this study, we examined associations between socioeconomic status (SES) and amygdala volume by age across childhood and adolescence to test whether socioeconomic disadvantage would be associated with larger amygdala volume at younger ages but with smaller amygdala volume at older ages. We then examined whether SES and amygdala volume were associated with children's levels of anxiety and depression. Participants were 3- to 21-year-olds from the Pediatric Imaging, Neurocognition, and Genetics study (N = 1,196), which included structural magnetic resonance imaging. A subsample (n = 327; 7-21 years of age) completed self-report measures of anxiety and depression. Lower family income and parental education were significantly associated with smaller amygdala volume in adolescence (13-21 years) but not significantly associated with amygdala volume at younger ages (3-12 years). Lower parental education, but not family income, was significantly associated with higher levels of anxiety and depression, even after accounting for family history of anxiety/depression. Smaller amygdala volume was significantly associated with higher levels of depression, even after accounting for parental education and family history of anxiety/depression. These findings suggest that associations between SES and amygdala structure may vary by age. In addition, smaller amygdala volume may be linked with an increased risk for depression in children and adolescents.
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Affiliation(s)
- Emily C Merz
- a Department of Epidemiology , Columbia University Medical Center
| | | | - Kimberly G Noble
- c Department of Biobehavioral Sciences , Teachers College, Columbia University, for the Pediatric Imaging, Neurocognition, and Genetics Study
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16
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Morris JK, Vidoni ED, Johnson DK, Van Sciver A, Mahnken JD, Honea RA, Wilkins HM, Brooks WM, Billinger SA, Swerdlow RH, Burns JM. Aerobic exercise for Alzheimer's disease: A randomized controlled pilot trial. PLoS One 2017; 12:e0170547. [PMID: 28187125 PMCID: PMC5302785 DOI: 10.1371/journal.pone.0170547] [Citation(s) in RCA: 173] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 01/05/2017] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND There is increasing interest in the role of physical exercise as a therapeutic strategy for individuals with Alzheimer's disease (AD). We assessed the effect of 26 weeks (6 months) of a supervised aerobic exercise program on memory, executive function, functional ability and depression in early AD. METHODS AND FINDINGS This study was a 26-week randomized controlled trial comparing the effects of 150 minutes per week of aerobic exercise vs. non-aerobic stretching and toning control intervention in individuals with early AD. A total of 76 well-characterized older adults with probable AD (mean age 72.9 [7.7]) were enrolled and 68 participants completed the study. Exercise was conducted with supervision and monitoring by trained exercise specialists. Neuropsychological tests and surveys were conducted at baseline,13, and 26 weeks to assess memory and executive function composite scores, functional ability (Disability Assessment for Dementia), and depressive symptoms (Cornell Scale for Depression in Dementia). Cardiorespiratory fitness testing and brain MRI was performed at baseline and 26 weeks. Aerobic exercise was associated with a modest gain in functional ability (Disability Assessment for Dementia) compared to individuals in the ST group (X2 = 8.2, p = 0.02). There was no clear effect of intervention on other primary outcome measures of Memory, Executive Function, or depressive symptoms. However, secondary analyses revealed that change in cardiorespiratory fitness was positively correlated with change in memory performance and bilateral hippocampal volume. CONCLUSIONS Aerobic exercise in early AD is associated with benefits in functional ability. Exercise-related gains in cardiorespiratory fitness were associated with improved memory performance and reduced hippocampal atrophy, suggesting cardiorespiratory fitness gains may be important in driving brain benefits. TRIAL REGISTRATION ClinicalTrials.gov NCT01128361.
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Affiliation(s)
- Jill K. Morris
- University of Kansas Alzheimer’s Disease Center, Fairway, KS, United States of America
| | - Eric D. Vidoni
- University of Kansas Alzheimer’s Disease Center, Fairway, KS, United States of America
| | - David K. Johnson
- Department of Psychology, University of Kansas, Lawrence, KS, United States of America
| | - Angela Van Sciver
- University of Kansas Alzheimer’s Disease Center, Fairway, KS, United States of America
| | - Jonathan D. Mahnken
- Department of Biostatistics, University of Kansas Medical Center, Kansas City, KS, United States of America
| | - Robyn A. Honea
- University of Kansas Alzheimer’s Disease Center, Fairway, KS, United States of America
| | - Heather M. Wilkins
- University of Kansas Alzheimer’s Disease Center, Fairway, KS, United States of America
| | - William M. Brooks
- University of Kansas Alzheimer’s Disease Center, Fairway, KS, United States of America
- Hoglund Brain Imaging Center, University of Kansas Medical Center, Kansas City, KS, United States of America
| | - Sandra A. Billinger
- Department of Physical Therapy and Rehabilitation Science, University of Kansas Medical Center, Kansas City, KS, United States of America
| | - Russell H. Swerdlow
- University of Kansas Alzheimer’s Disease Center, Fairway, KS, United States of America
| | - Jeffrey M. Burns
- University of Kansas Alzheimer’s Disease Center, Fairway, KS, United States of America
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17
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Aguirre GK, Datta R, Benson NC, Prasad S, Jacobson SG, Cideciyan AV, Bridge H, Watkins KE, Butt OH, Dain AS, Brandes L, Gennatas ED. Patterns of Individual Variation in Visual Pathway Structure and Function in the Sighted and Blind. PLoS One 2016; 11:e0164677. [PMID: 27812129 PMCID: PMC5094697 DOI: 10.1371/journal.pone.0164677] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2016] [Accepted: 09/28/2016] [Indexed: 11/18/2022] Open
Abstract
Many structural and functional brain alterations accompany blindness, with substantial individual variation in these effects. In normally sighted people, there is correlated individual variation in some visual pathway structures. Here we examined if the changes in brain anatomy produced by blindness alter the patterns of anatomical variation found in the sighted. We derived eight measures of central visual pathway anatomy from a structural image of the brain from 59 sighted and 53 blind people. These measures showed highly significant differences in mean size between the sighted and blind cohorts. When we examined the measurements across individuals within each group we found three clusters of correlated variation, with V1 surface area and pericalcarine volume linked, and independent of the thickness of V1 cortex. These two clusters were in turn relatively independent of the volumes of the optic chiasm and lateral geniculate nucleus. This same pattern of variation in visual pathway anatomy was found in the sighted and the blind. Anatomical changes within these clusters were graded by the timing of onset of blindness, with those subjects with a post-natal onset of blindness having alterations in brain anatomy that were intermediate to those seen in the sighted and congenitally blind. Many of the blind and sighted subjects also contributed functional MRI measures of cross-modal responses within visual cortex, and a diffusion tensor imaging measure of fractional anisotropy within the optic radiations and the splenium of the corpus callosum. We again found group differences between the blind and sighted in these measures. The previously identified clusters of anatomical variation were also found to be differentially related to these additional measures: across subjects, V1 cortical thickness was related to cross-modal activation, and the volume of the optic chiasm and lateral geniculate was related to fractional anisotropy in the visual pathway. Our findings show that several of the structural and functional effects of blindness may be reduced to a smaller set of dimensions. It also seems that the changes in the brain that accompany blindness are on a continuum with normal variation found in the sighted.
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Affiliation(s)
- Geoffrey K. Aguirre
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
- * E-mail:
| | - Ritobrato Datta
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Noah C. Benson
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Sashank Prasad
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Samuel G. Jacobson
- Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Artur V. Cideciyan
- Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Holly Bridge
- FMRIB Centre, Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, United Kingdom
| | - Kate E. Watkins
- Department of Experimental Psychology, University of Oxford, Oxford, OX1 3UD, United Kingdom
| | - Omar H. Butt
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Aleksandra S. Dain
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Lauren Brandes
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
| | - Efstathios D. Gennatas
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States of America
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18
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Ursache A, Noble KG. Socioeconomic status, white matter, and executive function in children. Brain Behav 2016; 6:e00531. [PMID: 27781144 PMCID: PMC5064342 DOI: 10.1002/brb3.531] [Citation(s) in RCA: 119] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2016] [Revised: 05/31/2016] [Accepted: 06/03/2016] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND A growing body of evidence links socioeconomic status (SES) to children's brain structure. Few studies, however, have specifically investigated relations of SES to white matter structure. Further, although several studies have demonstrated that family SES is related to development of brain areas that support executive functions (EF), less is known about the role that white matter structure plays in the relation of SES to EF. One possibility is that white matter differences may partially explain SES disparities in EF (i.e., a mediating relationship). Alternatively, SES may differentially shape brain-behavior relations such that the relation of white matter structure to EF may differ as a function of SES (i.e., a moderating relationship). METHOD In a diverse sample of 1082 children and adolescents aged 3-21 years, we examined socioeconomic disparities in white matter macrostructure and microstructure. We further investigated relations between family SES, children's white matter volume and integrity in tracts supporting EF, and performance on EF tasks. RESULTS Socioeconomic status was associated with fractional anisotropy (FA) and volume in multiple white matter tracts. Additionally, family income moderated the relation between white matter structure and cognitive flexibility. Specifically, across multiple tracts of interest, lower FA or lower volume was associated with reduced cognitive flexibility among children from lower income families. In contrast, children from higher income families showed preserved cognitive flexibility in the face of low white matter FA or volume. SES factors did not mediate or moderate links between white matter and either working memory or inhibitory control. CONCLUSIONS This work adds to a growing body of literature suggesting that the socioeconomic contexts in which children develop not only shape cognitive functioning and its underlying neurobiology, but may also shape the relations between brain and behavior.
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19
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Piccolo LR, Merz EC, He X, Sowell ER, Noble KG. Age-Related Differences in Cortical Thickness Vary by Socioeconomic Status. PLoS One 2016; 11:e0162511. [PMID: 27644039 PMCID: PMC5028041 DOI: 10.1371/journal.pone.0162511] [Citation(s) in RCA: 108] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Accepted: 08/15/2016] [Indexed: 11/25/2022] Open
Abstract
Recent findings indicate robust associations between socioeconomic status (SES) and brain structure in children, raising questions about the ways in which SES may modify structural brain development. In general, cortical thickness and surface area develop in nonlinear patterns across childhood and adolescence, with developmental patterns varying to some degree by cortical region. Here, we examined whether age-related nonlinear changes in cortical thickness and surface area varied by SES, as indexed by family income and parental education. We hypothesized that SES disparities in age-related change may be particularly evident for language- and literacy-supporting cortical regions. Participants were 1148 typically-developing individuals between 3 and 20 years of age. Results indicated that SES factors moderate patterns of age-associated change in cortical thickness but not surface area. Specifically, at lower levels of SES, associations between age and cortical thickness were curvilinear, with relatively steep age-related decreases in cortical thickness earlier in childhood, and subsequent leveling off during adolescence. In contrast, at high levels of SES, associations between age and cortical thickness were linear, with consistent reductions across the age range studied. Notably, this interaction was prominent in the left fusiform gyrus, a region that is critical for reading development. In a similar pattern, SES factors significantly moderated linear age-related change in left superior temporal gyrus, such that higher SES was linked with steeper age-related decreases in cortical thickness in this region. These findings suggest that SES may moderate patterns of age-related cortical thinning, especially in language- and literacy-supporting cortical regions.
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Affiliation(s)
- Luciane R. Piccolo
- Department of Biobehavioral Sciences, Teachers College, Columbia University, New York, New York, United States of America
| | - Emily C. Merz
- Department of Epidemiology, Columbia University Medical Center, New York, New York, United States of America
| | - Xiaofu He
- Department of Psychiatry, Columbia University, New York State Psychiatric Institute, New York, New York, United States of America
| | - Elizabeth R. Sowell
- Department of Pediatrics, Children’s Hospital Los Angeles, Los Angeles, California, United States of America
| | - Kimberly G. Noble
- Department of Biobehavioral Sciences, Teachers College, Columbia University, New York, New York, United States of America
- * E-mail:
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20
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Tadayon SH, Vaziri-Pashkam M, Kahali P, Ansari Dezfouli M, Abbassian A. Common Genetic Variant in VIT Is Associated with Human Brain Asymmetry. Front Hum Neurosci 2016; 10:236. [PMID: 27252636 PMCID: PMC4877381 DOI: 10.3389/fnhum.2016.00236] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2015] [Accepted: 05/04/2016] [Indexed: 11/22/2022] Open
Abstract
Brain asymmetry varies across individuals. However, genetic factors contributing to this normal variation are largely unknown. Here we studied variation of cortical surface area asymmetry in a large sample of subjects. We performed principal component analysis (PCA) to capture correlated asymmetry variation across cortical regions. We found that caudal and rostral anterior cingulate together account for a substantial part of asymmetry variation among individuals. To find SNPs associated with this subset of brain asymmetry variation we performed a genome-wide association study followed by replication in an independent cohort. We identified one SNP (rs11691187) that had genome-wide significant association (PCombined = 2.40e-08). The rs11691187 is in the first intron of VIT. In a follow-up analysis, we found that VIT gene expression is associated with brain asymmetry in six donors of the Allen Human Brain Atlas. Based on these findings we suggest that VIT contributes to normal brain asymmetry variation. Our results can shed light on disorders associated with altered brain asymmetry.
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Affiliation(s)
- Sayed H Tadayon
- School of Cognitive Sciences, Institute for Research in Fundamental SciencesTehran, Iran; School of Mathematics, Institute for Research in Fundamental SciencesTehran, Iran
| | - Maryam Vaziri-Pashkam
- Vision Sciences Laboratory, Department of Psychology, Harvard University Cambridge, MA, USA
| | - Pegah Kahali
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences Tehran, Iran
| | - Mitra Ansari Dezfouli
- Department of Cell and Molecular Biology, School of Biology, College of Science, University of Tehran Tehran, Iran
| | - Abdolhossein Abbassian
- School of Cognitive Sciences, Institute for Research in Fundamental SciencesTehran, Iran; School of Mathematics, Institute for Research in Fundamental SciencesTehran, Iran
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21
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Jernigan TL, Brown TT, Bartsch H, Dale AM. Toward an integrative science of the developing human mind and brain: Focus on the developing cortex. Dev Cogn Neurosci 2016; 18:2-11. [PMID: 26347228 PMCID: PMC4762760 DOI: 10.1016/j.dcn.2015.07.008] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2015] [Revised: 07/17/2015] [Accepted: 07/28/2015] [Indexed: 11/24/2022] Open
Abstract
Based on the Huttenlocher lecture, this article describes the need for a more integrative scientific paradigm for addressing important questions raised by key observations made over 2 decades ago. Among these are the early descriptions by Huttenlocher of variability in synaptic density in cortex of postmortem brains of children of different ages and the almost simultaneous reports of cortical volume reductions on MR imaging in children and adolescents. In spite of much progress in developmental neurobiology, developmental cognitive neuroscience, and behavioral and imaging genetics, we still do not know how these early observations relate to each other. It is argued that large scale, collaborative research programs are needed to establish the associations between behavioral differences among children and imaging biomarkers, and to link the latter to cellular changes in the developing brain. Examples of progress and challenges remaining are illustrated with data from the Pediatric Imaging, Neurocognition, and Genetics Project (PING).
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Affiliation(s)
- Terry L Jernigan
- Center for Human Development, University of California, San Diego, La Jolla, CA, United States; Department of Cognitive Science, University of California, San Diego, La Jolla, CA, United States; Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States; Department of Radiology, University of California, San Diego, La Jolla, CA, United States.
| | - Timothy T Brown
- Multimodal Imaging Laboratory, University of California, San Diego, La Jolla, CA, United States; Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | - Hauke Bartsch
- Multimodal Imaging Laboratory, University of California, San Diego, La Jolla, CA, United States
| | - Anders M Dale
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, United States; Department of Radiology, University of California, San Diego, La Jolla, CA, United States; Multimodal Imaging Laboratory, University of California, San Diego, La Jolla, CA, United States; Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
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22
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Douet V, Chang L, Lee K, Ernst T. ERBB4 polymorphism and family history of psychiatric disorders on age-related cortical changes in healthy children. Brain Imaging Behav 2016; 9:128-40. [PMID: 25744101 DOI: 10.1007/s11682-015-9363-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Genetic variations in ERBB4 were associated with increased susceptibility for schizophrenia (SCZ) and bipolar disorders (BPD). Structural imaging studies showed cortical abnormalities in adolescents and adults with SCZ or BPD. However, less is known about subclinical cortical changes or the influence of ERBB4 on cortical development. 971 healthy children (ages 3-20 years old; 462 girls and 509 boys) were genotyped for the ERBB4-rs7598440 variants, had structural MRI, and cognitive evaluation (NIH Toolbox ®). We investigated the effects of ERBB4 variants and family history of SCZ and/or BPD (FH) on cortical measures and cognitive performances across ages 3-20 years using a general additive model. Variations in ERBB4 and FH impact differentially the age-related cortical changes in regions often affected by SCZ and BPD. The ERBB4-TT-risk genotype children with no FH had subtle cortical changes across the age span, primarily located in the left temporal lobe and superior parietal cortex. In contrast, the TT-risk genotype children with FH had more pronounced age-related changes, mainly in the frontal lobes compared to the non-risk genotype children. Interactive effects of age, FH and ERBB4 variations were also found on episodic memory and working memory, which are often impaired in SCZ and BPD. Healthy children carrying the risk-genotype in ERBB4 and/or with FH had cortical measures resembling those reported in SCZ or BPD. These subclinical cortical variations may provide early indicators for increased risk of psychiatric disorders and improve our understanding of the effect of the NRG1-ERBB4 pathway on brain development.
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Affiliation(s)
- Vanessa Douet
- Department of Medicine, John A. Burns School of Medicine, University of Hawaii and The Queen's Medical Center, 1356 Lusitana Street, UH Tower, Room 716, Honolulu, HI, 96813, USA,
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23
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Giddaluru S, Espeseth T, Salami A, Westlye LT, Lundquist A, Christoforou A, Cichon S, Adolfsson R, Steen VM, Reinvang I, Nilsson LG, Le Hellard S, Nyberg L. Genetics of structural connectivity and information processing in the brain. Brain Struct Funct 2016; 221:4643-4661. [PMID: 26852023 PMCID: PMC5102980 DOI: 10.1007/s00429-016-1194-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Accepted: 01/22/2016] [Indexed: 12/20/2022]
Abstract
Understanding the genetic factors underlying brain structural connectivity is a major challenge in imaging genetics. Here, we present results from genome-wide association studies (GWASs) of whole-brain white matter (WM) fractional anisotropy (FA), an index of microstructural coherence measured using diffusion tensor imaging. Data from independent GWASs of 355 Swedish and 250 Norwegian healthy adults were integrated by meta-analysis to enhance power. Complementary GWASs on behavioral data reflecting processing speed, which is related to microstructural properties of WM pathways, were performed and integrated with WM FA results via multimodal analysis to identify shared genetic associations. One locus on chromosome 17 (rs145994492) showed genome-wide significant association with WM FA (meta P value = 1.87 × 10-08). Suggestive associations (Meta P value <1 × 10-06) were observed for 12 loci, including one containing ZFPM2 (lowest meta P value = 7.44 × 10-08). This locus was also implicated in multimodal analysis of WM FA and processing speed (lowest Fisher P value = 8.56 × 10-07). ZFPM2 is relevant in specification of corticothalamic neurons during brain development. Analysis of SNPs associated with processing speed revealed association with a locus that included SSPO (lowest meta P value = 4.37 × 10-08), which has been linked to commissural axon growth. An intergenic SNP (rs183854424) 14 kb downstream of CSMD1, which is implicated in schizophrenia, showed suggestive evidence of association in the WM FA meta-analysis (meta P value = 1.43 × 10-07) and the multimodal analysis (Fisher P value = 1 × 10-07). These findings provide novel data on the genetics of WM pathways and processing speed, and highlight a role of ZFPM2 and CSMD1 in information processing in the brain.
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Affiliation(s)
- Sudheer Giddaluru
- Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, 5021, Bergen, Norway.,K.G.Jebsen Center for Psychosis Research and the Norwegian Center for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, 5021, Bergen, Norway
| | - Thomas Espeseth
- K.G. Jebsen Center for Psychosis Research, Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, 0424, Oslo, Norway.,Department of Psychology, University of Oslo, 0317, Oslo, Norway
| | - Alireza Salami
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, 90187, Umeå, Sweden.,Aging Research Center, Karolinska Institutet and Stockholm University, 11330, Stockholm, Sweden
| | - Lars T Westlye
- K.G. Jebsen Center for Psychosis Research, Norwegian Center for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, 0424, Oslo, Norway.,Department of Psychology, University of Oslo, 0317, Oslo, Norway
| | - Anders Lundquist
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, 90187, Umeå, Sweden.,Department of Statistics, USBF, Umeå University, 90187, Umeå, Sweden
| | - Andrea Christoforou
- Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, 5021, Bergen, Norway.,K.G.Jebsen Center for Psychosis Research and the Norwegian Center for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, 5021, Bergen, Norway
| | - Sven Cichon
- Division of Medical Genetics, Department of Biomedicine, University of Basel, 4058, Basel, Switzerland.,Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, 52425, Juelich, Germany.,Department of Genomics, Life and Brain Center, University of Bonn, 53127, Bonn, Germany
| | - Rolf Adolfsson
- Department of Clinical Sciences, Psychiatry, Umeå University, 90187, Umeå, Sweden
| | - Vidar M Steen
- Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, 5021, Bergen, Norway.,K.G.Jebsen Center for Psychosis Research and the Norwegian Center for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, 5021, Bergen, Norway
| | - Ivar Reinvang
- Department of Psychology, University of Oslo, 0317, Oslo, Norway
| | - Lars Göran Nilsson
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, 90187, Umeå, Sweden.,ARC, Karolinska Institutet, Stockholm, Sweden
| | - Stéphanie Le Hellard
- Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, 5021, Bergen, Norway.,K.G.Jebsen Center for Psychosis Research and the Norwegian Center for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, 5021, Bergen, Norway
| | - Lars Nyberg
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, 90187, Umeå, Sweden. .,Department of Radiation Sciences, Umeå University, 90187, Umeå, Sweden. .,Department of Integrative Medical Biology, Umeå University, 90187, Umeå, Sweden.
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V1 surface size predicts GABA concentration in medial occipital cortex. Neuroimage 2016; 124:654-662. [DOI: 10.1016/j.neuroimage.2015.09.036] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2015] [Revised: 08/27/2015] [Accepted: 09/08/2015] [Indexed: 12/21/2022] Open
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Bergmann J, Genç E, Kohler A, Singer W, Pearson J. Smaller Primary Visual Cortex Is Associated with Stronger, but Less Precise Mental Imagery. Cereb Cortex 2015; 26:3838-50. [DOI: 10.1093/cercor/bhv186] [Citation(s) in RCA: 69] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
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26
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Saykin AJ, Shen L, Yao X, Kim S, Nho K, Risacher SL, Ramanan VK, Foroud TM, Faber KM, Sarwar N, Munsie LM, Hu X, Soares HD, Potkin SG, Thompson PM, Kauwe JSK, Kaddurah-Daouk R, Green RC, Toga AW, Weiner MW. Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans. Alzheimers Dement 2015; 11:792-814. [PMID: 26194313 PMCID: PMC4510473 DOI: 10.1016/j.jalz.2015.05.009] [Citation(s) in RCA: 202] [Impact Index Per Article: 22.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2015] [Revised: 05/08/2015] [Accepted: 05/08/2015] [Indexed: 01/01/2023]
Abstract
INTRODUCTION Genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) have been crucial in advancing the understanding of Alzheimer's disease (AD) pathophysiology. Here, we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans. METHODS Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing data have been obtained and disseminated. RESULTS ADNI genetic data have been downloaded thousands of times, and >300 publications have resulted, including reports of large-scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies used ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first whole exome and whole genome sequencing data sets and reports in healthy controls, mild cognitive impairment, and AD. DISCUSSION Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multiomics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological processes. Fortunately, a broad swath of the scientific community has accepted this grand challenge.
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Affiliation(s)
- Andrew J Saykin
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
| | - Li Shen
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Xiaohui Yao
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; School of Informatics and Computing, Indiana University, Purdue University - Indianapolis, Indianapolis, IN, USA
| | - Sungeun Kim
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kwangsik Nho
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Shannon L Risacher
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Vijay K Ramanan
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Tatiana M Foroud
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kelley M Faber
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | | | - Xiaolan Hu
- Bristol-Myers Squibb, Wallingford, CT, USA
| | | | - Steven G Potkin
- Department of Psychiatry and Human Behavior, University of California - Irvine, Irvine, CA, USA
| | - Paul M Thompson
- Department of Neurology, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA; Imaging Genetics Center, Keck School of Medicine of USC, University of Southern California, Marina del Rey, CA, USA
| | - John S K Kauwe
- Department of Biology, Brigham Young University, Provo, UT, USA; Department of Neuroscience, Brigham Young University, Provo, UT, USA
| | - Rima Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA; Duke Institute for Brain Sciences, Duke University, Durham, NC, USA
| | - Robert C Green
- Partners Center for Personalized Genetic Medicine, Boston, MA, USA; Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Arthur W Toga
- Laboratory of Neuroimaging, Institute for Neuroimaging and Neuroinformatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Michael W Weiner
- Department of Radiology, University of California-San Francisco, San Francisco, CA, USA; Department of Medicine, University of California-San Francisco, San Francisco, CA, USA; Department of Psychiatry, University of California-San Francisco, San Francisco, CA, USA; Center for Imaging of Neurodegenerative Diseases, San Francisco VA Medical Center, San Francisco, CA, USA
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Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ, Cedarbaum J, Green RC, Harvey D, Jack CR, Jagust W, Luthman J, Morris JC, Petersen RC, Saykin AJ, Shaw L, Shen L, Schwarz A, Toga AW, Trojanowski JQ. 2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception. Alzheimers Dement 2015; 11:e1-120. [PMID: 26073027 PMCID: PMC5469297 DOI: 10.1016/j.jalz.2014.11.001] [Citation(s) in RCA: 203] [Impact Index Per Article: 22.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 04/18/2013] [Indexed: 01/18/2023]
Abstract
The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.
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Affiliation(s)
- Michael W Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA; Department of Radiology, University of California, San Francisco, CA, USA; Department of Medicine, University of California, San Francisco, CA, USA; Department of Psychiatry, University of California, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, CA, USA.
| | - Dallas P Veitch
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA
| | - Paul S Aisen
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Laurel A Beckett
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | - Nigel J Cairns
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, Saint Louis, MO, USA; Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Jesse Cedarbaum
- Neurology Early Clinical Development, Biogen Idec, Cambridge, MA, USA
| | - Robert C Green
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health Sciences, University of California, Davis, CA, USA
| | | | - William Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - Johan Luthman
- Neuroscience Clinical Development, Neuroscience & General Medicine Product Creation Unit, Eisai Inc., Philadelphia, PA, USA
| | - John C Morris
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | | | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Leslie Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Li Shen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Adam Schwarz
- Tailored Therapeutics, Eli Lilly and Company, Indianapolis, IN, USA
| | - Arthur W Toga
- Laboratory of Neuroimaging, Institute of Neuroimaging and Informatics, Keck School of Medicine of University of Southern California, Los Angeles, CA, USA
| | - John Q Trojanowski
- Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Alzheimer's Disease Core Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Udall Parkinson's Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Noble KG, Houston SM, Brito NH, Bartsch H, Kan E, Kuperman JM, Akshoomoff N, Amaral DG, Bloss CS, Libiger O, Schork NJ, Murray SS, Casey BJ, Chang L, Ernst TM, Frazier JA, Gruen JR, Kennedy DN, Van Zijl P, Mostofsky S, Kaufmann WE, Kenet T, Dale AM, Jernigan TL, Sowell ER. Family income, parental education and brain structure in children and adolescents. Nat Neurosci 2015; 18:773-8. [PMID: 25821911 PMCID: PMC4414816 DOI: 10.1038/nn.3983] [Citation(s) in RCA: 685] [Impact Index Per Article: 76.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2014] [Accepted: 02/27/2015] [Indexed: 01/18/2023]
Abstract
Socioeconomic disparities are associated with differences in cognitive development. The extent to which this translates to disparities in brain structure is unclear. Here, we investigated relationships between socioeconomic factors and brain morphometry, independently of genetic ancestry, among a cohort of 1099 typically developing individuals between 3 and 20 years. Income was logarithmically associated with brain surface area. Specifically, among children from lower income families, small differences in income were associated with relatively large differences in surface area, whereas, among children from higher income families, similar income increments were associated with smaller differences in surface area. These relationships were most prominent in regions supporting language, reading, executive functions and spatial skills; surface area mediated socioeconomic differences in certain neurocognitive abilities. These data indicate that income relates most strongly to brain structure among the most disadvantaged children. Potential implications are discussed.
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Affiliation(s)
- Kimberly G Noble
- 1] College of Physicians and Surgeons, Columbia University, New York, New York, USA. [2] Teachers College, Columbia University, New York, New York, USA
| | - Suzanne M Houston
- 1] Department of Psychology, University of Southern California, Los Angeles, California, USA. [2] The Saban Research Institute of Children's Hospital, Los Angeles, California, USA. [3] Department of Pediatrics of the Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Natalie H Brito
- Robert Wood Johnson Health and Society Scholar Program, Columbia University, New York, New York, USA
| | - Hauke Bartsch
- Stein Institute for Research on Aging, University of California, San Diego, La Jolla, California, USA
| | - Eric Kan
- 1] The Saban Research Institute of Children's Hospital, Los Angeles, California, USA. [2] Department of Pediatrics of the Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Joshua M Kuperman
- 1] Multimodal Imaging Laboratory, University of California, San Diego, La Jolla, California, USA. [2] Department of Radiology, University of California, San Diego, La Jolla, California, USA. [3] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA
| | - Natacha Akshoomoff
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Center for Human Development, University of California, San Diego, La Jolla, California, USA. [3] Department of Psychiatry, University of California, San Diego, La Jolla, California, USA
| | - David G Amaral
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] The MIND Institute, University of California at Davis, Davis, California, USA
| | - Cinnamon S Bloss
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] The Qualcomm Institute, University of California, San Diego, La Jolla, California, USA
| | | | - Nicholas J Schork
- Human Biology, J. Craig Venter Institute, University of California, San Diego, La Jolla, California, USA
| | - Sarah S Murray
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Department of Pathology, University of California, San Diego, La Jolla, California, USA
| | - B J Casey
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Weill Medical College of Cornell University, New York, New York, USA
| | - Linda Chang
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Department of Medicine, John A. Burns School of Medicine, University of Hawaii and the Queen's Medical Center, Honolulu, Hawaii, USA
| | - Thomas M Ernst
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Department of Medicine, John A. Burns School of Medicine, University of Hawaii and the Queen's Medical Center, Honolulu, Hawaii, USA
| | - Jean A Frazier
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] University of Massachusetts Medical School, Worcester, Massachusetts, USA
| | - Jeffrey R Gruen
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut, USA. [3] Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, USA. [4] Department of Investigative Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
| | - David N Kennedy
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] University of Massachusetts Medical School, Worcester, Massachusetts, USA
| | - Peter Van Zijl
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA. [3] Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Stewart Mostofsky
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Walter E Kaufmann
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Department of Neurology, Boston Children's Hospital, Boston, Massachusetts, USA. [3] Harvard Medical School, Boston, Massachusetts, USA
| | - Tal Kenet
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Harvard Medical School, Boston, Massachusetts, USA. [3] Department of Neurology, Massachusetts General Hospital, Massachusetts, USA
| | - Anders M Dale
- 1] Multimodal Imaging Laboratory, University of California, San Diego, La Jolla, California, USA. [2] Department of Radiology, University of California, San Diego, La Jolla, California, USA. [3] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [4] Department of Cognitive Science, University of California, San Diego, La Jolla, California, USA. [5] Department of Neurology, Department of Neurosciences, University of California, San Diego, La Jolla, California, USA. [6] Center for Translational Imaging and Personalized Medicine, University of California San Diego, La Jolla, California, USA
| | - Terry L Jernigan
- 1] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA. [2] Center for Human Development, University of California, San Diego, La Jolla, California, USA. [3] Department of Psychiatry, University of California, San Diego, La Jolla, California, USA. [4] Department of Cognitive Science, University of California, San Diego, La Jolla, California, USA
| | - Elizabeth R Sowell
- 1] The Saban Research Institute of Children's Hospital, Los Angeles, California, USA. [2] Department of Pediatrics of the Keck School of Medicine, University of Southern California, Los Angeles, California, USA. [3] The Pediatric Imaging, Neurocognition, and Genetics Study, San Diego, California, USA
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Strike LT, Couvy-Duchesne B, Hansell NK, Cuellar-Partida G, Medland SE, Wright MJ. Genetics and Brain Morphology. Neuropsychol Rev 2015; 25:63-96. [DOI: 10.1007/s11065-015-9281-1] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2014] [Accepted: 02/08/2015] [Indexed: 12/17/2022]
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Future advances. HANDBOOK OF CLINICAL NEUROLOGY 2015. [PMID: 25726297 DOI: 10.1016/b978-0-444-62630-1.00038-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register]
Abstract
Future advances in the auditory systems are difficult to predict, and only educated guesses are possible. It is expected that innovative technologies in the field of neuroscience will be applied to the auditory system. Optogenetics, Brainbow, and CLARITY will improve our knowledge of the working of neural auditory networks and the relationship between sound and language, providing a dynamic picture of the brain in action. CLARITY makes brain tissue transparent and offers a three-dimensional view of neural networks, which, combined with genetically labeling neurons with multiple, distinct colors (Optogenetics), will provide detailed information of the complex brain system. Molecular functional magnetic resonance imaging (MRI) will allow the study of neurotransmitters detectable by MRI and their function in the auditory pathways. The Human Connectome project will study the patterns of distributed brain activity that underlie virtually all aspects of cognition and behavior and determine if abnormalities in the distributed patterns of activity may result in hearing and behavior disorders. Similarly, the programs of Big Brain and ENIGMA will improve our understanding of auditory disorders. New stem-cell therapy and gene therapies therapy may bring about a partial restoration of hearing for impaired patients by inducing regeneration of cochlear hair cells.
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Thompson PM, Stein JL, Medland SE, Hibar DP, Vasquez AA, Renteria ME, Toro R, Jahanshad N, Schumann G, Franke B, Wright MJ, Martin NG, Agartz I, Alda M, Alhusaini S, Almasy L, Almeida J, Alpert K, Andreasen NC, Andreassen OA, Apostolova LG, Appel K, Armstrong NJ, Aribisala B, Bastin ME, Bauer M, Bearden CE, Bergmann Ø, Binder EB, Blangero J, Bockholt HJ, Bøen E, Bois C, Boomsma DI, Booth T, Bowman IJ, Bralten J, Brouwer RM, Brunner HG, Brohawn DG, Buckner RL, Buitelaar J, Bulayeva K, Bustillo JR, Calhoun VD, Cannon DM, Cantor RM, Carless MA, Caseras X, Cavalleri GL, Chakravarty MM, Chang KD, Ching CRK, Christoforou A, Cichon S, Clark VP, Conrod P, Coppola G, Crespo-Facorro B, Curran JE, Czisch M, Deary IJ, de Geus EJC, den Braber A, Delvecchio G, Depondt C, de Haan L, de Zubicaray GI, Dima D, Dimitrova R, Djurovic S, Dong H, Donohoe G, Duggirala R, Dyer TD, Ehrlich S, Ekman CJ, Elvsåshagen T, Emsell L, Erk S, Espeseth T, Fagerness J, Fears S, Fedko I, Fernández G, Fisher SE, Foroud T, Fox PT, Francks C, Frangou S, Frey EM, Frodl T, Frouin V, Garavan H, Giddaluru S, Glahn DC, Godlewska B, Goldstein RZ, Gollub RL, Grabe HJ, Grimm O, Gruber O, Guadalupe T, Gur RE, Gur RC, Göring HHH, Hagenaars S, Hajek T, Hall GB, Hall J, Hardy J, Hartman CA, Hass J, Hatton SN, Haukvik UK, Hegenscheid K, Heinz A, Hickie IB, Ho BC, Hoehn D, Hoekstra PJ, Hollinshead M, Holmes AJ, Homuth G, Hoogman M, Hong LE, Hosten N, Hottenga JJ, Hulshoff Pol HE, Hwang KS, Jack CR, Jenkinson M, Johnston C, Jönsson EG, Kahn RS, Kasperaviciute D, Kelly S, Kim S, Kochunov P, Koenders L, Krämer B, Kwok JBJ, Lagopoulos J, Laje G, Landen M, Landman BA, Lauriello J, Lawrie SM, Lee PH, Le Hellard S, Lemaître H, Leonardo CD, Li CS, Liberg B, Liewald DC, Liu X, Lopez LM, Loth E, Lourdusamy A, Luciano M, Macciardi F, Machielsen MWJ, MacQueen GM, Malt UF, Mandl R, Manoach DS, Martinot JL, Matarin M, Mather KA, Mattheisen M, Mattingsdal M, Meyer-Lindenberg A, McDonald C, McIntosh AM, McMahon FJ, McMahon KL, Meisenzahl E, Melle I, Milaneschi Y, Mohnke S, Montgomery GW, Morris DW, Moses EK, Mueller BA, Muñoz Maniega S, Mühleisen TW, Müller-Myhsok B, Mwangi B, Nauck M, Nho K, Nichols TE, Nilsson LG, Nugent AC, Nyberg L, Olvera RL, Oosterlaan J, Ophoff RA, Pandolfo M, Papalampropoulou-Tsiridou M, Papmeyer M, Paus T, Pausova Z, Pearlson GD, Penninx BW, Peterson CP, Pfennig A, Phillips M, Pike GB, Poline JB, Potkin SG, Pütz B, Ramasamy A, Rasmussen J, Rietschel M, Rijpkema M, Risacher SL, Roffman JL, Roiz-Santiañez R, Romanczuk-Seiferth N, Rose EJ, Royle NA, Rujescu D, Ryten M, Sachdev PS, Salami A, Satterthwaite TD, Savitz J, Saykin AJ, Scanlon C, Schmaal L, Schnack HG, Schork AJ, Schulz SC, Schür R, Seidman L, Shen L, Shoemaker JM, Simmons A, Sisodiya SM, Smith C, Smoller JW, Soares JC, Sponheim SR, Sprooten E, Starr JM, Steen VM, Strakowski S, Strike L, Sussmann J, Sämann PG, Teumer A, Toga AW, Tordesillas-Gutierrez D, Trabzuni D, Trost S, Turner J, Van den Heuvel M, van der Wee NJ, van Eijk K, van Erp TGM, van Haren NEM, van ‘t Ent D, van Tol MJ, Valdés Hernández MC, Veltman DJ, Versace A, Völzke H, Walker R, Walter H, Wang L, Wardlaw JM, Weale ME, Weiner MW, Wen W, Westlye LT, Whalley HC, Whelan CD, White T, Winkler AM, Wittfeld K, Woldehawariat G, Wolf C, Zilles D, Zwiers MP, Thalamuthu A, Schofield PR, Freimer NB, Lawrence NS, Drevets W. The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data. Brain Imaging Behav 2014; 8:153-82. [PMID: 24399358 PMCID: PMC4008818 DOI: 10.1007/s11682-013-9269-5] [Citation(s) in RCA: 494] [Impact Index Per Article: 49.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
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Affiliation(s)
- Paul M. Thompson
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Jason L. Stein
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095 Netherlands
| | - Sarah E. Medland
- QIMR Berghofer Medical Research Institute, Quantitative Genetics, Brisbane, Australia
| | - Derrek P. Hibar
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Alejandro Arias Vasquez
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Miguel E. Renteria
- QIMR Berghofer Medical Research Institute, Quantitative Genetics, Brisbane, Australia
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- CNRS URA 2182 ‘Genes, synapses and cognition’, Institut Pasteur, Paris, France
- Sorbonne Paris Cité, Human Genetics and Cognitive Functions, Université Paris Diderot, Paris, France
| | - Neda Jahanshad
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Gunter Schumann
- MRC-SGDP Centre, Institute of Psychiatry, King’s College London, London, UK
| | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Margaret J. Wright
- QIMR Berghofer Medical Research Institute, Neuroimaging Genetics, Brisbane, Australia
| | - Nicholas G. Martin
- QIMR Berghofer Medical Research Institute, Genetic Epidemiology, Brisbane, Australia
| | - Ingrid Agartz
- Department of Clinical Neuroscience, Karolinska Institutet and Hospital, Stockholm, Sweden
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia Canada
| | - Saud Alhusaini
- Department of Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland
- Department of Neurology and NeuroSurgery, McGill University, Montreal, Quebec Canada
| | - Laura Almasy
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Jorge Almeida
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia Canada
| | - Kathryn Alpert
- Departments of Psychiatry and Behavioral Sciences and Radiology, Northwestern University, Chicago, IL USA
| | | | - Ole A. Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Liana G. Apostolova
- Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, CA USA
| | - Katja Appel
- Department of Psychiatry and Psychotherapy, University of Greifswald, Greifswald, Germany
| | - Nicola J. Armstrong
- School of Mathematics and Statistics, University of Sydney, Sydney, Australia
| | - Benjamin Aribisala
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Scotland, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
| | - Mark E. Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Michael Bauer
- Department of Psychiatry and Psychotherapy, Carl Gustav Carus University Hospital, Dresden, Germany
| | - Carrie E. Bearden
- Department of Psychiatry and Biobehavioral Sciences and the Center for Neurobehavioral Genetics, The Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA USA
- Department of Psychology, UCLA, Los Angeles, CA USA
| | - Ørjan Bergmann
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | - John Blangero
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | | | - Erlend Bøen
- Department of Psychosomatic Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Catherine Bois
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Dorret I. Boomsma
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Tom Booth
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
| | - Ian J. Bowman
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Janita Bralten
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands
| | - Rachel M. Brouwer
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Han G. Brunner
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - David G. Brohawn
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA USA
| | - Randy L. Buckner
- Massachusetts General Hospital, Boston, MA USA
- Center for Brain Science, Harvard University, Cambridge, MA USA
| | - Jan Buitelaar
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, The Netherlands
| | - Kazima Bulayeva
- N. I. Vavilov Institute of General Genetics, Russian Academy of Sciences, Gubkin str. 3, Moscow, 119991 Russia
| | - Juan R. Bustillo
- Department of Psychiatry, University of New Mexico, Albuquerque, NM USA
| | - Vince D. Calhoun
- The Mind Research Network, Albuquerque, NM USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM USA
| | - Dara M. Cannon
- Clinical Neuroimaging Laboratory, National University of Ireland Galway, University Road, Galway, Ireland
| | - Rita M. Cantor
- Center for Neurobehavioral Genetics, University of California, Los Angeles, CA USA
| | - Melanie A. Carless
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Xavier Caseras
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Gianpiero L. Cavalleri
- Department of Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland
| | - M. Mallar Chakravarty
- The Kimel Family Translational Imaging Genetics Laboratory, The Centre for Addiction and Mental Health, Toronto, ON Canada
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON Canada
| | - Kiki D. Chang
- Department of Psychiatry, Stanford University School of Medicine, Stanford, CA USA
| | - Christopher R. K. Ching
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Andrea Christoforou
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Dr Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Sven Cichon
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Institute for Neuroscience and Medicine (INM-1), Centre Jülich, Jülich, Germany
- Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Vincent P. Clark
- Department of Psychology, University of New Mexico, Albuquerque, NM USA
| | - Patricia Conrod
- CHU Sainte Justine University Hospital Research Center, Montreal, QC Canada
- Addictions Department, King’s Health Partners, King’s College London, London, UK
| | - Giovanni Coppola
- Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, CA USA
- Department of Psychiatry and Biobehavioral Sciences and the Center for Neurobehavioral Genetics, The Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA USA
| | - Benedicto Crespo-Facorro
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IFIMAV, School of Medicine, University of Cantabria, Santander, Spain
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Joanne E. Curran
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | | | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
| | - Eco J. C. de Geus
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Anouk den Braber
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
| | | | - Chantal Depondt
- Department of Neurology, Hopital Erasme, Universite Libre de Bruxelles, 1070 Brussels, Belgium
| | - Lieuwe de Haan
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
| | | | - Danai Dima
- MRC-SGDP Centre, Institute of Psychiatry, King’s College London, London, UK
| | - Rali Dimitrova
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Srdjan Djurovic
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Hongwei Dong
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Gary Donohoe
- Clinical Neuroimaging Laboratory, National University of Ireland Galway, University Road, Galway, Ireland
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Institute for Molecular Medicine and Trinity College Institute for Neuroscience, Trinity College, Dublin, Ireland
| | | | - Thomas D. Dyer
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Stefan Ehrlich
- MGH/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA USA
- University Hospital C.G. Carus, Department of Child and Adolescent Psychiatry, Dresden University of Technology, Dresden, Germany
| | - Carl Johan Ekman
- Department of Clinical Neuroscience, Karolinska Institutet and Hospital, Stockholm, Sweden
| | - Torbjørn Elvsåshagen
- Department of Psychosomatic Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Louise Emsell
- Clinical Neuroimaging Laboratory, National University of Ireland Galway, University Road, Galway, Ireland
| | - Susanne Erk
- Department of Psychiatry and Psychotherapy, Charité, Universitaetsmedizin Berlin, Charitè Campus Mitte, Berlin, Germany
| | - Thomas Espeseth
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Jesen Fagerness
- Massachusetts General Hospital, Boston, MA USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA USA
| | - Scott Fears
- Center for Neurobehavioral Genetics, University of California, Los Angeles, CA USA
- Department of Psychiatry and Biobehavioral Sciences and the Center for Neurobehavioral Genetics, The Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA USA
| | - Iryna Fedko
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
| | - Guillén Fernández
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands
| | - Simon E. Fisher
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
- Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
| | - Peter T. Fox
- Research Imaging Institute, UT Health Science Center at San Antonio, San Antonio, TX USA
- South Texas Veterans Health Care Center, San Antonio, TX USA
- South Texas Veterans Health Care System, San Antonio, TX USA
| | - Clyde Francks
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
- Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
| | - Sophia Frangou
- Psychosis Research Unit, Mount Sinai School of Medicine, New York, NY USA
| | - Eva Maria Frey
- Department of Psychiatry and Psychotherapy, University Regensburg, Regensburg, Germany
| | - Thomas Frodl
- Department of Psychiatry and Psychotherapy, University Regensburg, Regensburg, Germany
- Department of Psychiatry and Psychotherapy, Trinity College, University Dublin, Dublin, Germany
| | - Vincent Frouin
- Neurospin, Commissariat à l’Energie Atomique, Paris, France
| | - Hugh Garavan
- Department of Psychiatry, UHC University of Vermont, Bergen, VT USA
| | - Sudheer Giddaluru
- Dr Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - David C. Glahn
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, CT USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA
| | | | - Rita Z. Goldstein
- Department of Psychiatry and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Randy L. Gollub
- MGH/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University of Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), University of Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, Helios Hospital Stralsund, Stralsund, Germany
| | - Oliver Grimm
- Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Oliver Gruber
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry, Georg August University, Goettingen, Germany
| | - Tulio Guadalupe
- Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA USA
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA USA
- Philadelphia Veterans Administration Medical Center, Philadelphia, PA USA
| | - Harald H. H. Göring
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Saskia Hagenaars
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia Canada
| | - Geoffrey B. Hall
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON Canada
| | - Jeremy Hall
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
| | - John Hardy
- Department of Molecular Neuroscience, UCL Institute, London, UK
| | - Catharina A. Hartman
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Johanna Hass
- University Hospital C.G. Carus, Department of Child and Adolescent Psychiatry, Dresden University of Technology, Dresden, Germany
| | - Sean N. Hatton
- The Brain and Mind Research Institute, University of Sydney, Sydney, Australia
| | - Unn K. Haukvik
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Katrin Hegenscheid
- Department of Diagnostic Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité, Universitaetsmedizin Berlin, Charitè Campus Mitte, Berlin, Germany
| | - Ian B. Hickie
- The Brain and Mind Research Institute, University of Sydney, Sydney, Australia
| | - Beng-Choon Ho
- Department of Psychiatry, University of Iowa, Iowa City, IA USA
| | - David Hoehn
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Pieter J. Hoekstra
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Marisa Hollinshead
- MGH/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA USA
- Center for Brain Science, Harvard University, Cambridge, MA USA
| | - Avram J. Holmes
- MGH/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
- Center for Brain Science, Harvard University, Cambridge, MA USA
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Martine Hoogman
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - L. Elliot Hong
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD USA
| | - Norbert Hosten
- Department of Diagnostic Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
| | | | - Kristy S. Hwang
- Oakland University William Beaumont School of Medicine, Rochester Hills, MI USA
| | | | - Mark Jenkinson
- Oxford Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK
| | - Caroline Johnston
- National Institute of Health Research Biomedical Research Centre for Mental Health, South London and Maudsley National Health Service Foundation Trust, London, UK
- King’s College London, Institute of Psychiatry, London, UK
| | - Erik G. Jönsson
- Department of Clinical Neuroscience, Karolinska Institutet and Hospital, Stockholm, Sweden
| | - René S. Kahn
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dalia Kasperaviciute
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
| | - Sinead Kelly
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Institute for Molecular Medicine and Trinity College Institute for Neuroscience, Trinity College, Dublin, Ireland
| | - Sungeun Kim
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD USA
| | - Laura Koenders
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Bernd Krämer
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry, Georg August University, Goettingen, Germany
| | - John B. J. Kwok
- Neuroscience Research Australia, Sydney, Australia
- School of Medical Sciences, University of New South Wales, Sydney, Australia
- School of Medical Sciences, University of New South Wales, Kensington, NSW Australia
| | - Jim Lagopoulos
- The Brain and Mind Research Institute, University of Sydney, Sydney, Australia
| | - Gonzalo Laje
- Maryland Institute for Neuroscience and Development (MIND), Chevy Chase, MD USA
| | - Mikael Landen
- Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | | | - John Lauriello
- Department of Psychiatry, University of Missouri, Columbia, MO USA
| | - Stephen M. Lawrie
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Phil H. Lee
- Broad Institute of Harvard and MIT, Boston, MA USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA USA
| | - Stephanie Le Hellard
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Dr Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Herve Lemaître
- Research Unit 1000, Neuroimaging and Psychiatry, INSERM-CEA-Faculté de Médecine Paris Sud University-Paris Descartes University, Maison de Solenn Paris, SHFJ Orsay, Paris, France
| | - Cassandra D. Leonardo
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Chiang-shan Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA
| | - Benny Liberg
- Department of Clinical Neuroscience, Karolinska Institutet and Hospital, Stockholm, Sweden
| | - David C. Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
| | - Xinmin Liu
- Mood and Anxiety Disorders Section, Human Genetics Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Dept of Health and Human Services, Bethesda, MD USA
- Taub Institute for Research on Alzheimer Disease and the Aging Brain, Columbia University Medical Center, New York, NY USA
| | - Lorna M. Lopez
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Eva Loth
- MRC-SGDP Centre, Institute of Psychiatry, King’s College London, London, UK
| | | | - Michelle Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
| | - Fabio Macciardi
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA USA
- Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy
| | | | - Glenda M. MacQueen
- Mathison Centre for Mental Health Research and Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta Canada
| | - Ulrik F. Malt
- Department of Psychosomatic Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - René Mandl
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Dara S. Manoach
- MGH/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - Jean-Luc Martinot
- Research Unit 1000, Neuroimaging and Psychiatry, INSERM-CEA-Faculté de Médecine Paris Sud University-Paris Descartes University, Maison de Solenn Paris, SHFJ Orsay, Paris, France
| | - Mar Matarin
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
| | - Karen A. Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Medicine, Sydney, New South Wales Australia
| | - Manuel Mattheisen
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Department of Genomic Mathematics, University of Bonn, Bonn, Germany
| | - Morten Mattingsdal
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Research Unit, Sorlandet Hospital HF, Kristiansand, Norway
| | - Andreas Meyer-Lindenberg
- Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Colm McDonald
- Clinical Neuroimaging Laboratory, National University of Ireland Galway, University Road, Galway, Ireland
| | - Andrew M. McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Francis J. McMahon
- Mood and Anxiety Disorders Section, Human Genetics Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Dept of Health and Human Services, Bethesda, MD USA
| | - Katie L. McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | | | - Ingrid Melle
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Yuri Milaneschi
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD USA
| | - Sebastian Mohnke
- Department of Psychiatry and Psychotherapy, Charité, Universitaetsmedizin Berlin, Charitè Campus Mitte, Berlin, Germany
| | - Grant W. Montgomery
- Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Australia
| | - Derek W. Morris
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Institute for Molecular Medicine and Trinity College Institute for Neuroscience, Trinity College, Dublin, Ireland
| | - Eric K. Moses
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
- Centre for Genetic Origins of Health and Disease, The University of Western Australia, Perth, Australia
| | - Bryon A. Mueller
- Department of Psychiatry, University of Minnesota Medical Center, Minneapolis, MN USA
| | - Susana Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Scotland, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
| | - Thomas W. Mühleisen
- Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Institute for Neuroscience and Medicine (INM-1), Centre Jülich, Jülich, Germany
| | - Bertram Müller-Myhsok
- Max Planck Institute of Psychiatry, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Benson Mwangi
- Department of Psychiatry and Behavioral Sciences, University of Texas Medical School, Houston, TX USA
- University of Texas Center of Excellence on Mood Disorders, Department of Psychiatry, UT Medical School, Houston, TX USA
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University of Greifswald, Greifswald, Germany
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN USA
| | - Thomas E. Nichols
- Department of Statistics & Warwick Manufacturing Group, The University of Warwick, Coventry, UK
| | - Lars-Göran Nilsson
- Department of Psychology, Stockholm University, Stockholm, Sweden
- Stockholm Brain Institute, Stockholm, Sweden
| | - Allison C. Nugent
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD USA
| | - Lars Nyberg
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
| | - Rene L. Olvera
- Department of Psychiatry, UT Health Science Center at San Antonio, San Antonio, TX USA
| | - Jaap Oosterlaan
- Department of Clinical Neuropsychology, VU University, Amsterdam, The Netherlands
| | - Roel A. Ophoff
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
- Center for Neurobehavioral Genetics, University of California, Los Angeles, CA USA
| | - Massimo Pandolfo
- Department of Neurology, Hopital Erasme, Universite Libre de Bruxelles, 1070 Brussels, Belgium
| | | | - Martina Papmeyer
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Tomas Paus
- Rotman Research Institute, University of Toronto, Toronto, ON Canada
| | - Zdenka Pausova
- The Hospital for Sick Children, University of Toronto, Toronto, ON Canada
| | - Godfrey D. Pearlson
- Department of Psychiatry and Psychotherapy, University of Greifswald, Greifswald, Germany
- Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, CT USA
| | - Brenda W. Penninx
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
| | - Charles P. Peterson
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
| | - Andrea Pfennig
- Department of Psychiatry and Psychotherapy, Carl Gustav Carus University Hospital, Dresden, Germany
| | - Mary Phillips
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
| | - G. Bruce Pike
- Department of Radiology, University of Calgary, Calgary, Alberta Canada
| | - Jean-Baptiste Poline
- Hellen Wills Neuroscience Institute, Brain Imaging Center, University of California at Berkeley, Berkeley, CA USA
| | - Steven G. Potkin
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA USA
| | - Benno Pütz
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Adaikalavan Ramasamy
- Department of Medical and Molecular Genetics, King’s College London, London, UK
- Reta Lila Weston Institute and Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Jerod Rasmussen
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA USA
| | - Marcella Rietschel
- Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Mark Rijpkema
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Shannon L. Risacher
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN USA
| | - Joshua L. Roffman
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
| | - Roberto Roiz-Santiañez
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IFIMAV, School of Medicine, University of Cantabria, Santander, Spain
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Nina Romanczuk-Seiferth
- Department of Psychiatry and Psychotherapy, Charité, Universitaetsmedizin Berlin, Charitè Campus Mitte, Berlin, Germany
| | - Emma J. Rose
- Transdisciplinary and Translational Prevention Program, RTI International, Baltimore, MD USA
| | - Natalie A. Royle
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
| | - Dan Rujescu
- Department of Psychiatry, University of Halle, Halle, Germany
| | - Mina Ryten
- Department of Molecular Neuroscience, UCL Institute, London, UK
- Department of Medical and Molecular Genetics, King’s College London, London, UK
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Medicine, Sydney, New South Wales Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, New South Wales Australia
| | - Alireza Salami
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | | | - Jonathan Savitz
- Laureate Institute for Brain Research, Tulsa, OK USA
- Faculty of Community Medicine, University of Tulsa, Tulsa, OK USA
| | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
| | - Cathy Scanlon
- Clinical Neuroimaging Laboratory, National University of Ireland Galway, University Road, Galway, Ireland
| | - Lianne Schmaal
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Hugo G. Schnack
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - S. Charles Schulz
- Department of Psychiatry, University of Minnesota Medical Center, Minneapolis, MN USA
| | - Remmelt Schür
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Larry Seidman
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA USA
- Department of Psychiatry, Harvard Medical School, Harvard University, Cambridge, MA USA
| | - Li Shen
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN USA
| | | | - Andrew Simmons
- Department of Neuroimaging, Institute of Psychiatry, King’s College London, London, UK
- NIHR Biomedical Research Centre for Mental Health at South London and Maudsley NHS Trust and Institute of Psychiatry, King’s College London, London, UK
| | - Sanjay M. Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
| | - Colin Smith
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Jordan W. Smoller
- Broad Institute of Harvard and MIT, Boston, MA USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA USA
| | - Jair C. Soares
- Department of Psychiatry and Behavioral Sciences, University of Texas Medical School, Houston, TX USA
| | - Scott R. Sponheim
- Department of Psychiatry, University of Minnesota Medical Center, Minneapolis, MN USA
- Minneapolis VA Health Care System, Minneapolis, MN USA
| | - Emma Sprooten
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA
| | - John M. Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
| | - Vidar M. Steen
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Dr Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Stephen Strakowski
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
| | - Lachlan Strike
- Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Australia
| | - Jessika Sussmann
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | | | - Alexander Teumer
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Arthur W. Toga
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
| | - Diana Tordesillas-Gutierrez
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IFIMAV, School of Medicine, University of Cantabria, Santander, Spain
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Daniah Trabzuni
- Department of Molecular Neuroscience, UCL Institute, London, UK
- Department of Genetics, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | - Sarah Trost
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry, Georg August University, Goettingen, Germany
| | - Jessica Turner
- The Mind Research Network, Albuquerque, NM USA
- Department of Psychology and Neuroscience Institute, Georgia State University, Atlanta, GA USA
| | | | - Nic J. van der Wee
- Department of Psychiatry and Leiden Institute for Brain and Cognition, Leiden University Medical Center, Leiden, The Netherlands
| | - Kristel van Eijk
- Department of Psychiatry, Rudolf Magnus Institute, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Theo G. M. van Erp
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA USA
| | | | - Dennis van ‘t Ent
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
| | - Marie-Jose van Tol
- Behavioural and Cognitive Neuroscience Neuroimaging Center, University Medical Center Groningen, Groningen, The Netherlands
| | - Maria C. Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
| | - Dick J. Veltman
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Amelia Versace
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
| | - Henry Völzke
- Institute for Community Medicine, University of Greifswald, Greifswald, Germany
| | - Robert Walker
- Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Charité, Universitaetsmedizin Berlin, Charitè Campus Mitte, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt University Berlin, Berlin, Germany
| | - Lei Wang
- Departments of Psychiatry and Behavioral Sciences and Radiology, Northwestern University, Chicago, IL USA
| | - Joanna M. Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Scotland, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
| | - Michael E. Weale
- Department of Medical and Molecular Genetics, King’s College London, London, UK
| | - Michael W. Weiner
- Departments of Radiology, Medicine, Psychiatry, University of California, San Francisco, CA USA
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Medicine, Sydney, New South Wales Australia
| | - Lars T. Westlye
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Heather C. Whalley
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Christopher D. Whelan
- Department of Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland
| | - Tonya White
- Department of Child and Adolescent Psychiatry, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | - Anderson M. Winkler
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA
- Oxford Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK
| | - Katharina Wittfeld
- German Center for Neurodegenerative Diseases (DZNE), University of Greifswald, Greifswald, Germany
| | - Girma Woldehawariat
- Mood and Anxiety Disorders Section, Human Genetics Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Dept of Health and Human Services, Bethesda, MD USA
| | | | - David Zilles
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry, Georg August University, Goettingen, Germany
| | - Marcel P. Zwiers
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
- Radboud University NijmegenDonders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, Psychiatry, University of New South Wales (UNSW), Sydney, Australia
| | - Peter R. Schofield
- Neuroscience Research Australia, Sydney, Australia
- School of Medical Sciences, University of New South Wales, Sydney, Australia
| | - Nelson B. Freimer
- Department of Psychiatry and Biobehavioral Sciences, UCLA School of Medicine, Los Angeles, CA USA
| | | | - Wayne Drevets
- Janssen Research & Development, of Johnson & Johnson, Inc., 1125 Trenton-Harbourton Road, Titusville, NJ 08560 USA
| | - the Alzheimer’s Disease Neuroimaging Initiative, EPIGEN Consortium, IMAGEN Consortium, Saguenay Youth Study (SYS) Group
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA 90033 USA
- Genetic Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Australia
- Broad Institute of Harvard and MIT, Boston, MA USA
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- CNRS URA 2182 ‘Genes, synapses and cognition’, Institut Pasteur, Paris, France
- Sorbonne Paris Cité, Human Genetics and Cognitive Functions, Université Paris Diderot, Paris, France
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, CT USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT USA
- Department of Psychiatry and Psychotherapy, University of Greifswald, Greifswald, Germany
- NORMENT, KG Jebsen Centre for Psychosis Research, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Molecular and Cellular Therapeutics, Royal College of Surgeons in Ireland, Dublin 2, Ireland
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX USA
- Department of Psychiatry, University of Iowa, Iowa City, IA USA
- Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, CA USA
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, 7 George Square, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Scotland, UK
- Brain Research Imaging Centre, The University of Edinburgh, Edinburgh, UK
- Max Planck Institute of Psychiatry, Munich, Germany
- The Mind Research Network, Albuquerque, NM USA
- Department of Biological Psychology, VU University, Neuroscience Campus, Amsterdam, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behavior, Nijmegen, The Netherlands
- Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
- Massachusetts General Hospital, Boston, MA USA
- Karakter Child and Adolescent Psychiatry University Center, Nijmegen, The Netherlands
- N. I. Vavilov Institute of General Genetics, Russian Academy of Sciences, Gubkin str. 3, Moscow, 119991 Russia
- Department of Psychiatry, University of New Mexico, Albuquerque, NM USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM USA
- Clinical Neuroimaging Laboratory, National University of Ireland Galway, University Road, Galway, Ireland
- Center for Neurobehavioral Genetics, University of California, Los Angeles, CA USA
- The Kimel Family Translational Imaging Genetics Laboratory, The Centre for Addiction and Mental Health, Toronto, ON Canada
- Dr Einar Martens Research Group for Biological Psychiatry, Department of Clinical Medicine, University of Bergen, Bergen, Norway
- Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
- Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Institute for Neuroscience and Medicine (INM-1), Centre Jülich, Jülich, Germany
- Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland
- Department of Psychiatry, Marqués de Valdecilla University Hospital, IFIMAV, School of Medicine, University of Cantabria, Santander, Spain
- Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
- Department of Psychology, The University of Edinburgh, Edinburgh, UK
- Department of Neurology, Hopital Erasme, Universite Libre de Bruxelles, 1070 Brussels, Belgium
- School of Psychology, University of Queensland, Brisbane, QLD 4072 Australia
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- Neuropsychiatric Genetics Research Group, Department of Psychiatry, Institute for Molecular Medicine and Trinity College Institute for Neuroscience, Trinity College, Dublin, Ireland
- MGH/HMS Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA USA
- University Hospital C.G. Carus, Department of Child and Adolescent Psychiatry, Dresden University of Technology, Dresden, Germany
- Department of Psychiatry and Psychotherapy, Charité, Universitaetsmedizin Berlin, Charitè Campus Mitte, Berlin, Germany
- Department of Psychology, University of Oslo, Oslo, Norway
- Max Planck Institute for Psycholinguistics, 6500 AH Nijmegen, The Netherlands
- Research Imaging Institute, UT Health Science Center at San Antonio, San Antonio, TX USA
- South Texas Veterans Health Care Center, San Antonio, TX USA
- Neurospin, Commissariat à l’Energie Atomique, Paris, France
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA USA
- German Center for Neurodegenerative Diseases (DZNE), University of Greifswald, Greifswald, Germany
- Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry, Georg August University, Goettingen, Germany
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
- Department of Molecular Neuroscience, UCL Institute, London, UK
- Department of Diagnostic Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
- National Institute of Health Research Biomedical Research Centre for Mental Health, South London and Maudsley National Health Service Foundation Trust, London, UK
- King’s College London, Institute of Psychiatry, London, UK
- Department of Clinical Neuroscience, Karolinska Institutet and Hospital, Stockholm, Sweden
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine, Indianapolis, IN USA
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA USA
- Mood and Anxiety Disorders Section, Human Genetics Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, US Dept of Health and Human Services, Bethesda, MD USA
- Taub Institute for Research on Alzheimer Disease and the Aging Brain, Columbia University Medical Center, New York, NY USA
- MRC-SGDP Centre, Institute of Psychiatry, King’s College London, London, UK
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA USA
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales Medicine, Sydney, New South Wales Australia
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Department of Genomic Mathematics, University of Bonn, Bonn, Germany
- Research Unit, Sorlandet Hospital HF, Kristiansand, Norway
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
- Ludwig-Maximilians-University (LMU), Munich, Germany
- Department of Psychiatry and Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
- Centre for Genetic Origins of Health and Disease, The University of Western Australia, Perth, Australia
- Department of Psychiatry, University of Minnesota Medical Center, Minneapolis, MN USA
- Department of Psychology, Stockholm University, Stockholm, Sweden
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
- Department of Psychiatry, UT Health Science Center at San Antonio, San Antonio, TX USA
- Rotman Research Institute, University of Toronto, Toronto, ON Canada
- The Hospital for Sick Children, University of Toronto, Toronto, ON Canada
- Department of Psychiatry and Leiden Institute for Brain and Cognition, Leiden University Medical Center, Leiden, The Netherlands
- Department of Medical and Molecular Genetics, King’s College London, London, UK
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, New South Wales Australia
- Laureate Institute for Brain Research, Tulsa, OK USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA USA
- Department of Neuroimaging, Institute of Psychiatry, King’s College London, London, UK
- NIHR Biomedical Research Centre for Mental Health at South London and Maudsley NHS Trust and Institute of Psychiatry, King’s College London, London, UK
- Minneapolis VA Health Care System, Minneapolis, MN USA
- Behavioural and Cognitive Neuroscience Neuroimaging Center, University Medical Center Groningen, Groningen, The Netherlands
- Institute for Community Medicine, University of Greifswald, Greifswald, Germany
- Departments of Radiology, Medicine, Psychiatry, University of California, San Francisco, CA USA
- Department of Child and Adolescent Psychiatry, Erasmus University Medical Centre, Rotterdam, The Netherlands
- Radboud University NijmegenDonders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands
- Oxford Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK
- Neuroscience Research Australia, Sydney, Australia
- School of Medical Sciences, University of New South Wales, Sydney, Australia
- Center for Brain Science, Harvard University, Cambridge, MA USA
- The Brain and Mind Research Institute, University of Sydney, Sydney, Australia
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, UK
- Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
- Department Early Psychosis, Academic Psychiatric Centre, AMC, UvA, Amsterdam, Netherlands
- EMGO + Institute, VU University Medical Center, Amsterdam, The Netherlands
- Cognitive Science Department, UC San Diego, La Jolla, CA USA
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Department of Clinical Neuropsychology, VU University, Amsterdam, The Netherlands
- Reta Lila Weston Institute and Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
- Department of Neurology and NeuroSurgery, McGill University, Montreal, Quebec Canada
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia Canada
- Department of Psychiatry, University of Oxford, Oxford, UK
- Department of Psychiatry and Behavioral Sciences, University of Texas Medical School, Houston, TX USA
- University of Texas Center of Excellence on Mood Disorders, Department of Psychiatry, UT Medical School, Houston, TX USA
- Department of Psychiatry and Biobehavioral Sciences and the Center for Neurobehavioral Genetics, The Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA USA
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD USA
- Berlin School of Mind and Brain, Humboldt University Berlin, Berlin, Germany
- Department of Psychiatry and Psychotherapy, Carl Gustav Carus University Hospital, Dresden, Germany
- Department of Psychiatry and Psychotherapy, Helios Hospital Stralsund, Stralsund, Germany
- Department of Psychiatry, Harvard Medical School, Harvard University, Cambridge, MA USA
- Department of Psychiatry, Brown University, Providence, RI USA
- Psychosis Research Unit, Mount Sinai School of Medicine, New York, NY USA
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA USA
- Philadelphia Veterans Administration Medical Center, Philadelphia, PA USA
- Department of Psychiatry and Psychotherapy, University Regensburg, Regensburg, Germany
- Department of Psychiatry and Psychotherapy, Trinity College, University Dublin, Dublin, Germany
- Stockholm Brain Institute, Stockholm, Sweden
- Department of Psychology and Neuroscience Institute, Georgia State University, Atlanta, GA USA
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON Canada
- Department of Psychology, University of New Mexico, Albuquerque, NM USA
- Department of Psychosomatic Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology, University of Calgary, Calgary, Alberta Canada
- Department of Statistics & Warwick Manufacturing Group, The University of Warwick, Coventry, UK
- Departments of Psychiatry and Behavioral Sciences and Radiology, Northwestern University, Chicago, IL USA
- Electrical Engineering, Vanderbilt University, Nashville, TN USA
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD USA
- Institute of Clinical Chemistry and Laboratory Medicine, University of Greifswald, Greifswald, Germany
- Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, ON Canada
- Faculty of Community Medicine, University of Tulsa, Tulsa, OK USA
- Maryland Institute for Neuroscience and Development (MIND), Chevy Chase, MD USA
- Mathison Centre for Mental Health Research and Education, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta Canada
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- MRC Centre for Neuropsychiatric Genetics and Genomics, Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, UK
- School of Medical Sciences, University of New South Wales, Kensington, NSW Australia
- Oakland University William Beaumont School of Medicine, Rochester Hills, MI USA
- CHU Sainte Justine University Hospital Research Center, Montreal, QC Canada
- Addictions Department, King’s Health Partners, King’s College London, London, UK
- South Texas Veterans Health Care System, San Antonio, TX USA
- Research Unit 1000, Neuroimaging and Psychiatry, INSERM-CEA-Faculté de Médecine Paris Sud University-Paris Descartes University, Maison de Solenn Paris, SHFJ Orsay, Paris, France
- Department of Genetics, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
- Department of Psychiatry, Rudolf Magnus Institute, University Medical Center Utrecht, Utrecht, The Netherlands
- School of Mathematics and Statistics, University of Sydney, Sydney, Australia
- School of Medicine, University of Nottingham, Nottingham, UK
- Department of Psychiatry, Stanford University School of Medicine, Stanford, CA USA
- Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Hellen Wills Neuroscience Institute, Brain Imaging Center, University of California at Berkeley, Berkeley, CA USA
- Department of Psychiatry, University of Missouri, Columbia, MO USA
- Departments of Psychiatry and Neurobiology, Yale University School of Medicine, New Haven, CT USA
- Mayo Clinic, Rochester, MN USA
- Transdisciplinary and Translational Prevention Program, RTI International, Baltimore, MD USA
- Department of Psychiatry and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Department of Psychiatry, University of Halle, Halle, Germany
- Advanced Biomedical Informatics Group, llc., Iowa City, IA USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095 Netherlands
- QIMR Berghofer Medical Research Institute, Quantitative Genetics, Brisbane, Australia
- QIMR Berghofer Medical Research Institute, Genetic Epidemiology, Brisbane, Australia
- QIMR Berghofer Medical Research Institute, Neuroimaging Genetics, Brisbane, Australia
- Department of Psychology, UCLA, Los Angeles, CA USA
- Department of Pharmacological and Biomolecular Sciences, University of Milan, Milan, Italy
- Dr. E. Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
- Department of Psychiatry, UHC University of Vermont, Bergen, VT USA
- Centre for Healthy Brain Ageing, Psychiatry, University of New South Wales (UNSW), Sydney, Australia
- Department of Psychiatry and Biobehavioral Sciences, UCLA School of Medicine, Los Angeles, CA USA
- School of Psychology, University of Exeter, Exeter, UK
- Janssen Research & Development, of Johnson & Johnson, Inc., 1125 Trenton-Harbourton Road, Titusville, NJ 08560 USA
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Shen L, Thompson PM, Potkin SG, Bertram L, Farrer LA, Foroud TM, Green RC, Hu X, Huentelman MJ, Kim S, Kauwe JSK, Li Q, Liu E, Macciardi F, Moore JH, Munsie L, Nho K, Ramanan VK, Risacher SL, Stone DJ, Swaminathan S, Toga AW, Weiner MW, Saykin AJ. Genetic analysis of quantitative phenotypes in AD and MCI: imaging, cognition and biomarkers. Brain Imaging Behav 2014; 8:183-207. [PMID: 24092460 PMCID: PMC3976843 DOI: 10.1007/s11682-013-9262-z] [Citation(s) in RCA: 121] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The Genetics Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI), formally established in 2009, aims to provide resources and facilitate research related to genetic predictors of multidimensional Alzheimer's disease (AD)-related phenotypes. Here, we provide a systematic review of genetic studies published between 2009 and 2012 where either ADNI APOE genotype or genome-wide association study (GWAS) data were used. We review and synthesize ADNI genetic associations with disease status or quantitative disease endophenotypes including structural and functional neuroimaging, fluid biomarker assays, and cognitive performance. We also discuss the diverse analytical strategies used in these studies, including univariate and multivariate analysis, meta-analysis, pathway analysis, and interaction and network analysis. Finally, we perform pathway and network enrichment analyses of these ADNI genetic associations to highlight key mechanisms that may drive disease onset and trajectory. Major ADNI findings included all the top 10 AD genes and several of these (e.g., APOE, BIN1, CLU, CR1, and PICALM) were corroborated by ADNI imaging, fluid and cognitive phenotypes. ADNI imaging genetics studies discovered novel findings (e.g., FRMD6) that were later replicated on different data sets. Several other genes (e.g., APOC1, FTO, GRIN2B, MAGI2, and TOMM40) were associated with multiple ADNI phenotypes, warranting further investigation on other data sets. The broad availability and wide scope of ADNI genetic and phenotypic data has advanced our understanding of the genetic basis of AD and has nominated novel targets for future studies employing next-generation sequencing and convergent multi-omics approaches, and for clinical drug and biomarker development.
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Affiliation(s)
- Li Shen
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Paul M. Thompson
- Imaging Genetics Center, Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095 USA
| | - Steven G. Potkin
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92617 USA
| | - Lars Bertram
- Neuropsychiatric Genetics Group, Max-Planck Institute for Molecular Genetics, Berlin, Germany
| | - Lindsay A. Farrer
- Biomedical Genetics L320, Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118 USA
| | - Tatiana M. Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202 USA
| | - Robert C. Green
- Division of Genetics and Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115 USA
| | - Xiaolan Hu
- Clinical Genetics, Exploratory Clinical & Translational Research, Bristol-Myers Squibbs, Pennington, NJ 08534 USA
| | - Matthew J. Huentelman
- Neurogenomics Division, The Translational Genomics Research Institute, Phoenix, AZ 85004 USA
| | - Sungeun Kim
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - John S. K. Kauwe
- Departments of Biology, Neuroscience, Brigham Young University, 675 WIDB, Provo, UT 84602 USA
| | - Qingqin Li
- Department of Neuroscience Biomarkers, Janssen Research and Development, LLC, Raritan, NJ 08869 USA
| | - Enchi Liu
- Biomarker Discovery, Janssen Alzheimer Immunotherapy Research and Development, LLC, South San Francisco, CA 94080 USA
| | - Fabio Macciardi
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92617 USA
- Department of Sciences and Biomedical Technologies, University of Milan, Segrate, MI Italy
| | - Jason H. Moore
- Department of Genetics, Computational Genetics Laboratory, Dartmouth Medical School, Lebanon, NH 03756 USA
| | - Leanne Munsie
- Tailored Therapeutics, Eli Lilly and Company, Indianapolis, IN 46285 USA
| | - Kwangsik Nho
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Vijay K. Ramanan
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202 USA
| | - Shannon L. Risacher
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - David J. Stone
- Merck Research Laboratories, 770 Sumneytown Pike, WP53B-120, West Point, PA 19486 USA
| | - Shanker Swaminathan
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Arthur W. Toga
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095 USA
| | - Michael W. Weiner
- Departments of Radiology, Medicine and Psychiatry, UC San Francisco, San Francisco, CA 94143 USA
| | - Andrew J. Saykin
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202 USA
| | - for the Alzheimer’s Disease Neuroimaging Initiative
- Center for Neuroimaging and Indiana Alzheimer’s Disease Center, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 355 W 16th Street, Suite 4100, Indianapolis, IN 46202 USA
- Imaging Genetics Center, Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095 USA
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92617 USA
- Neuropsychiatric Genetics Group, Max-Planck Institute for Molecular Genetics, Berlin, Germany
- Biomedical Genetics L320, Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118 USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202 USA
- Division of Genetics and Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115 USA
- Clinical Genetics, Exploratory Clinical & Translational Research, Bristol-Myers Squibbs, Pennington, NJ 08534 USA
- Neurogenomics Division, The Translational Genomics Research Institute, Phoenix, AZ 85004 USA
- Departments of Biology, Neuroscience, Brigham Young University, 675 WIDB, Provo, UT 84602 USA
- Department of Neuroscience Biomarkers, Janssen Research and Development, LLC, Raritan, NJ 08869 USA
- Biomarker Discovery, Janssen Alzheimer Immunotherapy Research and Development, LLC, South San Francisco, CA 94080 USA
- Department of Sciences and Biomedical Technologies, University of Milan, Segrate, MI Italy
- Department of Genetics, Computational Genetics Laboratory, Dartmouth Medical School, Lebanon, NH 03756 USA
- Tailored Therapeutics, Eli Lilly and Company, Indianapolis, IN 46285 USA
- Merck Research Laboratories, 770 Sumneytown Pike, WP53B-120, West Point, PA 19486 USA
- Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095 USA
- Departments of Radiology, Medicine and Psychiatry, UC San Francisco, San Francisco, CA 94143 USA
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Douet V, Chang L, Pritchett A, Lee K, Keating B, Bartsch H, Jernigan TL, Dale A, Akshoomoff N, Murray S, Bloss C, Kennedy DN, Amaral D, Gruen J, Kaufmann WE, Casey BJ, Sowell E, Ernst T. Schizophrenia-risk variant rs6994992 in the neuregulin-1 gene on brain developmental trajectories in typically developing children. Transl Psychiatry 2014; 4:e392. [PMID: 24865593 PMCID: PMC4035723 DOI: 10.1038/tp.2014.41] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2014] [Accepted: 04/22/2014] [Indexed: 11/09/2022] Open
Abstract
The neuregulin-1 (NRG1) gene is one of the best-validated risk genes for schizophrenia, and psychotic and bipolar disorders. The rs6994992 variant in the NRG1 promoter (SNP8NRG243177) is associated with altered frontal and temporal brain macrostructures and/or altered white matter density and integrity in schizophrenic adults, as well as healthy adults and neonates. However, the ages when these changes begin and whether neuroimaging phenotypes are associated with cognitive performance are not fully understood. Therefore, we investigated the association of the rs6994992 variant on developmental trajectories of brain macro- and microstructures, and their relationship with cognitive performance. A total of 972 healthy children aged 3-20 years had the genotype available for the NRG1-rs6994992 variant, and were evaluated with magnetic resonance imaging (MRI) and neuropsychological tests. Age-by-NRG1-rs6994992 interactions and genotype effects were assessed using a general additive model regression methodology, covaried for scanner type, socioeconomic status, sex and genetic ancestry factors. Compared with the C-carriers, children with the TT-risk-alleles had subtle microscopic and macroscopic changes in brain development that emerge or reverse during adolescence, a period when many psychiatric disorders are manifested. TT-children at late adolescence showed a lower age-dependent forniceal volume and lower fractional anisotropy; however, both measures were associated with better episodic memory performance. To our knowledge, we provide the first multimodal imaging evidence that genetic variation in NRG1 is associated with age-related changes on brain development during typical childhood and adolescence, and delineated the altered patterns of development in multiple brain regions in children with the T-risk allele(s).
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Affiliation(s)
- V Douet
- Department of Medicine, John A. Burns School of Medicine, University of Hawaii and Queen's Medical Center, Honolulu, HI, USA,Department of Medicine, John A. Burns School of Medicine, University of Hawaii and Queen's Medical Center, 1356 Lusitana Street, UH Tower, Room 716, Honolulu, HI 96813, USA. E-mail:
| | - L Chang
- Department of Medicine, John A. Burns School of Medicine, University of Hawaii and Queen's Medical Center, Honolulu, HI, USA
| | - A Pritchett
- Department of Medicine, John A. Burns School of Medicine, University of Hawaii and Queen's Medical Center, Honolulu, HI, USA
| | - K Lee
- Department of Medicine, John A. Burns School of Medicine, University of Hawaii and Queen's Medical Center, Honolulu, HI, USA
| | - B Keating
- Department of Medicine, John A. Burns School of Medicine, University of Hawaii and Queen's Medical Center, Honolulu, HI, USA
| | - H Bartsch
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - T L Jernigan
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA,Department of Psychiatry and Department of Cognitive Science, Center for Human Development, University of California, San Diego, La Jolla, CA, USA
| | - A Dale
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA,Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - N Akshoomoff
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA,Department of Psychiatry and Department of Cognitive Science, Center for Human Development, University of California, San Diego, La Jolla, CA, USA
| | - S Murray
- Scripps Genomic Medicine and Scripps Translational Science Institute, The Scripps Research Institute, La Jolla, CA, USA
| | - C Bloss
- Scripps Genomic Medicine and Scripps Translational Science Institute, The Scripps Research Institute, La Jolla, CA, USA
| | - D N Kennedy
- Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA, USA
| | - D Amaral
- Departments of Psychiatry and Behavioral Sciences, University of California, Davis, CA, USA
| | - J Gruen
- Departments of Pediatrics and Investigative Medicine, Child Health Research Center, Yale University School of Medicine, New Haven, CT, USA
| | - W E Kaufmann
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - B J Casey
- Sackler Institute for Developmental Psychobiology, Weil Cornell Medical College, New York, NY, USA
| | - E Sowell
- Department of Pediatrics, University of Southern California, and Children's Hospital, Los Angeles, CA, USA
| | - T Ernst
- Department of Medicine, John A. Burns School of Medicine, University of Hawaii and Queen's Medical Center, Honolulu, HI, USA
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35
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Corda D, Mosca MG, Ohshima N, Grauso L, Yanaka N, Mariggiò S. The emerging physiological roles of the glycerophosphodiesterase family. FEBS J 2014; 281:998-1016. [PMID: 24373430 DOI: 10.1111/febs.12699] [Citation(s) in RCA: 64] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2013] [Revised: 12/12/2013] [Accepted: 12/19/2013] [Indexed: 01/21/2023]
Abstract
The glycerophosphodiester phosphodiesterases are evolutionarily conserved proteins that have been linked to several patho/physiological functions, comprising bacterial pathogenicity and mammalian cell proliferation or differentiation. The bacterial enzymes do not show preferential substrate selectivities among the glycerophosphodiesters, and they are mainly dedicated to glycerophosphodiester hydrolysis, producing glycerophosphate and alcohols as the building blocks that are required for bacterial biosynthetic pathways. In some cases, this enzymatic activity has been demonstrated to contribute to bacterial pathogenicity, such as with Hemophilus influenzae. Mammalian glyerophosphodiesterases have high substrate specificities, even if the number of potential physiological substrates is continuously increasing. Some of these mammalian enzymes have been directly linked to cell differentiation, such as GDE2, which triggers motor neuron differentiation, and GDE3, the enzymatic activity of which is necessary and sufficient to induce osteoblast differentiation. Instead, GDE5 has been shown to inhibit skeletal muscle development independent of its enzymatic activity.
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Affiliation(s)
- Daniela Corda
- Institute of Protein Biochemistry, National Research Council, Naples, Italy
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36
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Klein D, Rotarska-Jagiela A, Genc E, Sritharan S, Mohr H, Roux F, Han CE, Kaiser M, Singer W, Uhlhaas PJ. Adolescent brain maturation and cortical folding: evidence for reductions in gyrification. PLoS One 2014; 9:e84914. [PMID: 24454765 PMCID: PMC3893168 DOI: 10.1371/journal.pone.0084914] [Citation(s) in RCA: 83] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2013] [Accepted: 11/28/2013] [Indexed: 01/29/2023] Open
Abstract
Evidence from anatomical and functional imaging studies have highlighted major modifications of cortical circuits during adolescence. These include reductions of gray matter (GM), increases in the myelination of cortico-cortical connections and changes in the architecture of large-scale cortical networks. It is currently unclear, however, how the ongoing developmental processes impact upon the folding of the cerebral cortex and how changes in gyrification relate to maturation of GM/WM-volume, thickness and surface area. In the current study, we acquired high-resolution (3 Tesla) magnetic resonance imaging (MRI) data from 79 healthy subjects (34 males and 45 females) between the ages of 12 and 23 years and performed whole brain analysis of cortical folding patterns with the gyrification index (GI). In addition to GI-values, we obtained estimates of cortical thickness, surface area, GM and white matter (WM) volume which permitted correlations with changes in gyrification. Our data show pronounced and widespread reductions in GI-values during adolescence in several cortical regions which include precentral, temporal and frontal areas. Decreases in gyrification overlap only partially with changes in the thickness, volume and surface of GM and were characterized overall by a linear developmental trajectory. Our data suggest that the observed reductions in GI-values represent an additional, important modification of the cerebral cortex during late brain maturation which may be related to cognitive development.
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Affiliation(s)
- Daniel Klein
- Department of Neurophysiology, Max-Planck Institute for Brain Research, Frankfurt am Main, Germany
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany
| | - Anna Rotarska-Jagiela
- Department of Neurophysiology, Max-Planck Institute for Brain Research, Frankfurt am Main, Germany
| | - Erhan Genc
- Department of Neurophysiology, Max-Planck Institute for Brain Research, Frankfurt am Main, Germany
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany
| | - Sharmili Sritharan
- Department of Neurophysiology, Max-Planck Institute for Brain Research, Frankfurt am Main, Germany
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany
| | - Harald Mohr
- Department of Neurocognitive Psychology, Institute of Psychology, Johann Wolfgang Goethe University, Frankfurt am Main, Germany
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Johann Wolfgang Goethe University, Frankfurt am Main, Germany
| | - Frederic Roux
- Department of Neurophysiology, Max-Planck Institute for Brain Research, Frankfurt am Main, Germany
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany
| | - Cheol E. Han
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, Republic of Korea
| | - Marcus Kaiser
- Department of Brain and Cognitive Sciences, Seoul National University, Seoul, Republic of Korea
- School of Computing Science and Institute of Neuroscience, Newcastle University, Newcastle, United Kingdom
| | - Wolf Singer
- Department of Neurophysiology, Max-Planck Institute for Brain Research, Frankfurt am Main, Germany
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany
- Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe University, Frankfurt am Main, Germany
| | - Peter J. Uhlhaas
- Department of Neurophysiology, Max-Planck Institute for Brain Research, Frankfurt am Main, Germany
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, United Kingdom
- * E-mail:
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Anderson ML, Finlay BL. Allocating structure to function: the strong links between neuroplasticity and natural selection. Front Hum Neurosci 2014; 7:918. [PMID: 24431995 PMCID: PMC3882658 DOI: 10.3389/fnhum.2013.00918] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2013] [Accepted: 12/15/2013] [Indexed: 11/23/2022] Open
Abstract
A central question in brain evolution is how species-typical behaviors, and the neural function-structure mappings supporting them, can be acquired and inherited. Advocates of brain modularity, in its different incarnations across scientific subfields, argue that natural selection must target domain-dedicated, separately modifiable neural subsystems, resulting in genetically-specified functional modules. In such modular systems, specification of neuron number and functional connectivity are necessarily linked. Mounting evidence, however, from allometric, developmental, comparative, systems-physiological, neuroimaging and neurological studies suggests that brain elements are used and reused in multiple functional systems. This variable allocation can be seen in short-term neuromodulation, in neuroplasticity over the lifespan and in response to damage. We argue that the same processes are evident in brain evolution. Natural selection must preserve behavioral functions that may co-locate in variable amounts with other functions. In genetics, the uses and problems of pleiotropy, the re-use of genes in multiple networks have been much discussed, but this issue has been sidestepped in neural systems by the invocation of modules. Here we highlight the interaction between evolutionary and developmental mechanisms to produce distributed and overlapping functional architectures in the brain. These adaptive mechanisms must be robust to perturbations that might disrupt critical information processing and action selection, but must also recognize useful new sources of information arising from internal genetic or environmental variability, when those appear. These contrasting properties of "robustness" and "evolvability" have been discussed for the basic organization of body plan and fundamental cell physiology. Here we extend them to the evolution and development, "evo-devo," of brain structure.
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Affiliation(s)
- Michael L. Anderson
- Department of Psychology, Franklin & Marshall CollegeLancaster, PA, USA
- Neuroscience and Cognitive Science Program, Institute for Advanced Computer Studies, University of MarylandCollege Park, MD, USA
| | - Barbara L. Finlay
- Behavioral and Evolutionary Neuroscience Group, Department of Psychology, Cornell UniversityIthaca, NY, USA
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Akshoomoff N, Newman E, Thompson WK, McCabe C, Bloss CS, Chang L, Amaral DG, Casey BJ, Ernst TM, Frazier JA, Gruen JR, Kaufmann WE, Kenet T, Kennedy DN, Libiger O, Mostofsky S, Murray SS, Sowell ER, Schork N, Dale AM, Jernigan TL. The NIH Toolbox Cognition Battery: results from a large normative developmental sample (PING). Neuropsychology 2014; 28:1-10. [PMID: 24219608 PMCID: PMC3925365 DOI: 10.1037/neu0000001] [Citation(s) in RCA: 130] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
OBJECTIVE The NIH Toolbox Cognition Battery (NTCB) was designed to provide a brief, efficient computerized test of key neuropsychological functions appropriate for use in children as young as 3 years of age. This report describes the performance of a large group of typically developing children and adolescents and examines the impact of age and sociocultural variables on test performance. METHOD The NTCB was administered to a sample of 1,020 typically developing males and females ranging in age from 3 to 20 years, diverse in terms of socioeconomic status (SES) and race/ethnicity, as part of the new publicly accessible Pediatric Imaging, Neurocognition, and Genetics (PING) data resource, at 9 sites across the United States. RESULTS General additive models of nonlinear age-functions were estimated from age-differences in test performance on the 8 NTCB subtests while controlling for family SES and genetic ancestry factors (GAFs). Age accounted for the majority of the variance across all NTCB scores, with additional significant contributions of gender on some measures, and of SES and race/ethnicity (GAFs) on all. After adjusting for age and gender, SES and GAFs explained a substantial proportion of the remaining unexplained variance in Picture Vocabulary scores. CONCLUSIONS The results highlight the sensitivity to developmental effects and efficiency of this new computerized assessment battery for neurodevelopmental research. Limitations are observed in the form of some ceiling effects in older children, some floor effects, particularly on executive function tests in the youngest participants, and evidence for variable measurement sensitivity to cultural/socioeconomic factors.
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Affiliation(s)
- Natacha Akshoomoff
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
- Center for Human Development, University of California, San Diego, La Jolla, CA
| | - Erik Newman
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
| | - Wesley K. Thompson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
- Stein Institute for Research on Aging, University of California, San Diego, La Jolla, CA
| | - Connor McCabe
- Center for Human Development, University of California, San Diego, La Jolla, CA
| | - Cinnamon S. Bloss
- Scripps Genomic Medicine, Scripps Translational Science Institute and Scripps Health, La Jolla, CA
| | - Linda Chang
- Department of Medicine, University of Hawaii and Queen’s Medical Center, Honolulu, HI
| | - David G. Amaral
- Department of Psychiatry and Behavioral Sciences and The M.I.N.D. Institute, University of California, Davis, Sacramento, CA
| | - B. J. Casey
- Sackler Institute for Developmental Psychobiology, Weil Cornell Medical College, New York, NY
| | - Thomas M. Ernst
- Department of Medicine, University of Hawaii and Queen’s Medical Center, Honolulu, HI
| | - Jean A. Frazier
- Department of Psychiatry, University of Massachusetts Medical School, Boston, MA
| | - Jeffrey R. Gruen
- Departments of Pediatrics and Genetics, Yale University School of Medicine, New Haven, CT
| | - Walter E. Kaufmann
- Kennedy Krieger Institute and Johns Hopkins University School of Medicine, Baltimore, MD
| | - Tal Kenet
- Department of Neurology and Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA
| | - David N. Kennedy
- Department of Psychiatry, University of Massachusetts Medical School, Boston, MA
| | - Ondrej Libiger
- Scripps Genomic Medicine, Scripps Translational Science Institute and Scripps Health, La Jolla, CA
| | - Stewart Mostofsky
- Kennedy Krieger Institute and Johns Hopkins University School of Medicine, Baltimore, MD
| | - Sarah S. Murray
- Scripps Genomic Medicine, Scripps Translational Science Institute and Scripps Health, La Jolla, CA
| | - Elizabeth R. Sowell
- Department of Pediatrics, University of Southern California, Los Angeles, CA and Children’s Hospital, Los Angeles, CA
| | - Nicholas Schork
- Scripps Genomic Medicine, Scripps Translational Science Institute and Scripps Health, La Jolla, CA
| | - Anders M. Dale
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
- Department of Radiology, University of California, San Diego, La Jolla, CA
| | - Terry L. Jernigan
- Department of Psychiatry, University of California, San Diego, La Jolla, CA
- Center for Human Development, University of California, San Diego, La Jolla, CA
- Department of Radiology, University of California, San Diego, La Jolla, CA
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA
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39
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Genç E, Bergmann J, Singer W, Kohler A. Surface area of early visual cortex predicts individual speed of traveling waves during binocular rivalry. ACTA ACUST UNITED AC 2013; 25:1499-508. [PMID: 24334918 DOI: 10.1093/cercor/bht342] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Binocular rivalry ensues when different images are presented to the 2 eyes with conscious perception alternating between the possible interpretations. For large rivalry displays, perceptual transitions are initiated at one location and spread to other parts of the visual field, a phenomenon termed "traveling wave." Previous studies investigated the underlying neural mechanisms of the traveling wave and surmised that primary visual cortex might play an important role. We used magnetic resonance imaging and behavioral measures in humans to explore how interindividual differences in observers' subjective experience of the wave are related to anatomical characteristics of cortical regions. We measured wave speed in participants and confirmed the long-term stability of the individual values. Retinotopic mapping was employed to delineate borders of visual areas V1-V3 in order to determine surface area and cortical thickness in those regions. Only the surface areas of V1 and V2, but not V3 showed a correlation with wave speed. For individuals with larger V1/V2 area, the traveling wave needed longer to spread across the same distance in visual space. Our results highlight the role of early visual areas in mediating binocular rivalry and suggest possible mechanisms for the correlation between surface area and the traveling waves.
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Affiliation(s)
- Erhan Genç
- Department of Neurophysiology, Max Planck Institute for Brain Research, D-60528 Frankfurt am Main, Germany Ruhr University Bochum, Biopsychology, D-44780 Bochum, Germany Brain Imaging Center Frankfurt, D-60528 Frankfurt am Main, Germany
| | - Johanna Bergmann
- Department of Neurophysiology, Max Planck Institute for Brain Research, D-60528 Frankfurt am Main, Germany Brain Imaging Center Frankfurt, D-60528 Frankfurt am Main, Germany School of Psychology, University of New South Wales, Sydney, Australia
| | - Wolf Singer
- Department of Neurophysiology, Max Planck Institute for Brain Research, D-60528 Frankfurt am Main, Germany Brain Imaging Center Frankfurt, D-60528 Frankfurt am Main, Germany Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, D-60528 Frankfurt am Main, Germany Frankfurt Institute for Advanced Studies, Goethe University, D-60438 Frankfurt am Main, Germany
| | - Axel Kohler
- Department of Neurophysiology, Max Planck Institute for Brain Research, D-60528 Frankfurt am Main, Germany Brain Imaging Center Frankfurt, D-60528 Frankfurt am Main, Germany Institute of Psychology, University of Münster, D-48149 Münster, Germany Current address: University of Osnabrück, Institute of Cognitive Science, Albrechtstr. 28, D-49076 Osnabrück, Germany
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40
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Hser YI, Chang L, Wang GJ, Li MD, Rawson R, Shoptaw S, Normand J, Tai B. Capacity building and collaborative research on cross-national studies in the Asian region. J Food Drug Anal 2013; 21:S117-S122. [PMID: 24567700 PMCID: PMC3931525 DOI: 10.1016/j.jfda.2013.09.048] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
To build capacity and collaborative research for future cross-national studies in the Asian and Pacific Islander (API) region, priority research topics were identified and discussed at the April 2013 Conference to Promote Global Health in Taipei. These topics included (1) Neuroscience on HIV/HCV and amphetamine-type stimulants (ATS), led by Drs. Linda Chang, Gene-Jack Wang, and Betty Tai; (2) ATS and mental health disorders, led by Drs. Richard Rawson and Wilson Compton; and (3) HIV/HCV transmission and social networks, led by Drs. Steven Shoptaw and Jacques Normand. Potential genetic studies spanning these topical areas as well as the importance of smoking cessation were further discussed, led by Dr. Ming Li. Additional priority research topics were also identified: (4) Drug use prevention, and (5) Family involvement to improve treatment adherence and recovery. Workgroups on these topics will be formed to prioritize research questions within the respective topical area and to determine the next steps. The ultimate goal of these workgroups is to stimulate collaboration that will eventually lead to research studies addressing critical issues related to the rising substance abuse and HIV infection rates in many Asian countries and, at the same time, to advance the scientific knowledge of substance abuse and HIV infection.
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41
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Weiner MW, Veitch DP, Aisen PS, Beckett LA, Cairns NJ, Green RC, Harvey D, Jack CR, Jagust W, Liu E, Morris JC, Petersen RC, Saykin AJ, Schmidt ME, Shaw L, Shen L, Siuciak JA, Soares H, Toga AW, Trojanowski JQ. The Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception. Alzheimers Dement 2013; 9:e111-94. [PMID: 23932184 DOI: 10.1016/j.jalz.2013.05.1769] [Citation(s) in RCA: 298] [Impact Index Per Article: 27.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Revised: 04/18/2013] [Indexed: 01/19/2023]
Abstract
The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2-year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI-2) in October 2010 through to 2016, with enrollment of an additional 550 participants.
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Affiliation(s)
- Michael W Weiner
- Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA.
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42
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Ciccarelli O. Comment on "Hierarchical genetic organization of human cortical surface area" by Chen et al. [Science 335 (2012) 1634-1636 (supporting information)]. Mult Scler Relat Disord 2013; 2:90-1. [PMID: 25877628 DOI: 10.1016/j.msard.2012.09.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2012] [Accepted: 09/26/2012] [Indexed: 10/27/2022]
Affiliation(s)
- Olga Ciccarelli
- Department of Brain Repair and Rehabilitation, Queen Square MS Centre, UCL Institute of Neurology, UCL, Queen Square, London WC1N 3BG, UK.
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Song C, Schwarzkopf DS, Rees G. Variability in visual cortex size reflects tradeoff between local orientation sensitivity and global orientation modulation. Nat Commun 2013; 4:2201. [PMID: 23887643 PMCID: PMC3731653 DOI: 10.1038/ncomms3201] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2012] [Accepted: 06/27/2013] [Indexed: 11/08/2022] Open
Abstract
The surface area of early visual cortices varies several fold across healthy adult humans and is genetically heritable. But the functional consequences of this anatomical variability are still largely unexplored. Here we show that interindividual variability in human visual cortical surface area reflects a tradeoff between sensitivity to visual details and susceptibility to visual context. Specifically, individuals with larger primary visual cortices can discriminate finer orientation differences, whereas individuals with smaller primary visual cortices experience stronger perceptual modulation by global orientation contexts. This anatomically correlated tradeoff between discrimination sensitivity and contextual modulation of orientation perception, however, does not generalize to contrast perception or luminance perception. Neural field simulations based on a scaling of intracortical circuits reproduce our empirical observations. Together our findings reveal a feature-specific shift in the scope of visual perception from context-oriented to detail-oriented with increased visual cortical surface area.
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Affiliation(s)
- Chen Song
- Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AR, UK.
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44
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Shen EH, Overly CC, Jones AR. The Allen Human Brain Atlas: comprehensive gene expression mapping of the human brain. Trends Neurosci 2012; 35:711-4. [PMID: 23041053 DOI: 10.1016/j.tins.2012.09.005] [Citation(s) in RCA: 142] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2012] [Revised: 09/17/2012] [Accepted: 09/18/2012] [Indexed: 10/27/2022]
Abstract
The Allen Human Brain Atlas is a freely available multimodal atlas of gene expression and anatomy comprising a comprehensive 'all genes-all structures' array-based dataset of gene expression and complementary in situ hybridization (ISH) gene expression studies targeting selected genes in specific brain regions. Available via the Allen Brain Atlas data portal (www.brain-map.org), the Atlas integrates structure, function, and gene expression data to accelerate basic and clinical research of the human brain in normal and disease states.
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Affiliation(s)
- Elaine H Shen
- Allen Institute for Brain Science, Seattle, WA 98103, USA.
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