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van Drunen L, Dobbelaar S, Crone EA, Wierenga LM. Genetic and environmental influences on structural brain development from childhood to adolescence: A longitudinal twin study on cortical thickness, surface area, and subcortical volume. Dev Cogn Neurosci 2024; 68:101407. [PMID: 38870602 PMCID: PMC11225697 DOI: 10.1016/j.dcn.2024.101407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 06/10/2024] [Accepted: 06/10/2024] [Indexed: 06/15/2024] Open
Abstract
The human brain undergoes structural development from childhood to adolescence, with specific regions in the sensorimotor, social, and affective networks continuing to grow into adulthood. While genetic and environmental factors contribute to individual differences in these brain trajectories, the extent remains understudied. Our longitudinal study, utilizing up to three biennial MRI scans (n=485), aimed to assess the genetic and environmental effects on brain structure (age 7) and development (ages 7-14) in these regions. Heritability estimates varied across brain regions, with all regions showing genetic influence (ranging from 18 % to 59 %) with additional shared environmental factors affecting the primary motor cortex (30 %), somatosensory cortex (35 %), DLPFC (5 %), TPJ (17 %), STS (17 %), precuneus (10 %), hippocampus (22 %), amygdala (5 %), and nucleus accumbens (10 %). Surface area was more genetically driven (38 %) than cortical thickness (14 %). Longitudinal brain changes were primarily driven by genetics (ranging from 1 % to 29 %), though shared environment factors (additionally) influenced the somatosensory cortex (11 %), DLPFC (7 %), cerebellum (28 %), TPJ (16 %), STS (20 %), and hippocampus (17 %). These findings highlight the importance of further investigating brain-behavior associations and the influence of enriched and deprived environments from childhood to adolescence. Ultimately, our study can provide insights for interventions aimed at supporting children's development.
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Affiliation(s)
- L van Drunen
- Leiden Consortium of Individual Development (L-CID), the Netherlands; Erasmus University Rotterdam, Social and Behavioral Sciences, the Netherlands; Leiden Institute for Brain and Cognition (LIBC), the Netherlands; Institute of Psychology, Leiden University, the Netherlands.
| | - S Dobbelaar
- Leiden Consortium of Individual Development (L-CID), the Netherlands; Erasmus University Rotterdam, Social and Behavioral Sciences, the Netherlands; Leiden Institute for Brain and Cognition (LIBC), the Netherlands; Institute of Psychology, Leiden University, the Netherlands
| | - E A Crone
- Leiden Consortium of Individual Development (L-CID), the Netherlands; Erasmus University Rotterdam, Social and Behavioral Sciences, the Netherlands; Leiden Institute for Brain and Cognition (LIBC), the Netherlands
| | - L M Wierenga
- Leiden Consortium of Individual Development (L-CID), the Netherlands; Leiden Institute for Brain and Cognition (LIBC), the Netherlands; Institute of Psychology, Leiden University, the Netherlands
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Zhao T, Guo H, Yang J, Cai A, Liu J, Zheng J, Xiao Y, Zhao P, Li Y, Luo X, Zhang X, Zhu R, Wang J, Wang F. Repetitive Transcranial Magnetic Stimulation Reversing Abnormal Brain Function in Mood Disorders with Early Life Stress: from preclinical models to clinical applications. Asian J Psychiatr 2024; 97:104092. [PMID: 38823081 DOI: 10.1016/j.ajp.2024.104092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 04/15/2024] [Accepted: 04/18/2024] [Indexed: 06/03/2024]
Abstract
BACKGROUND Early life stress (ELS) significantly increases the risk of mood disorders and affects the neurodevelopment of the primary cortex. HYPOTHESIS Modulating the primary cortex through neural intervention can ameliorate the impact of ELS on brain development and consequently alleviate its effects on mood disorders. METHOD We induced the chronic unpredictable mild stress (CUMS) model in adolescent rats, followed by applying repetitive transcranial magnetic stimulation (rTMS) to their primary cortex in early adulthood. To assess the applicability of primary cortex rTMS in humans, we recruited individuals aged 17-25 with mood disorders who had experienced ELS and performed primary cortex rTMS on them. Functional magnetic resonance imaging (fMRI) and depression-related behavioral and clinical symptoms were conducted in both rats and human subjects before and after the rTMS. RESULTS In animals, fMRI analysis revealed increased activation in the primary cortex of CUMS rats and decrease subcortical activation. Following the intervention of primary cortex rTMS, the abnormal functional activity was reversed. Similarly, in mood disorders patients with ELS, increased activation in the primary cortex and decreased activation in the frontal cortex were observed. During rTMS intervention, similar neuroimaging improvements were noted, particularly decreased activation in the primary cortex. This suggests that targeted rTMS in the primary cortex can reverse the abnormal neuroimaging. CONCLUSION This cross-species translational study has identified the primary cortex as a key region in mood disorders patients with ELS. Targeting the primary cortex with rTMS can correct abnormal functional activity while improving symptoms. Our study provides translational evidence for therapeutics targeting the ELS factor of mood disorders patients.
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Affiliation(s)
- Tongtong Zhao
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, PR China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, PR China
| | - Huiling Guo
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, PR China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, PR China; School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, PR China
| | - Jingyu Yang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, PR China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, PR China
| | - Aoling Cai
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, PR China; School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, PR China; Changzhou Medical Center, Changzhou No.2 People's Hospital, Nanjing Medical University, Changzhou, PR China
| | - Juan Liu
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, PR China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, PR China
| | - Junjie Zheng
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, PR China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, PR China
| | - Yao Xiao
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, PR China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, PR China
| | - Pengfei Zhao
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, PR China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, PR China
| | - Yifan Li
- Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Southeast University, Nanjing, Jiangsu 210096, China
| | - Xiongjian Luo
- Department of Psychosomatics and Psychiatry, Zhongda Hospital, School of Medicine, Advanced Institute for Life and Health, Southeast University, Nanjing, Jiangsu 210096, China
| | - Xizhe Zhang
- School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, PR China
| | - Rongxin Zhu
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, PR China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, PR China
| | - Jie Wang
- Academy of Integrative Medicine, College of Integrative Medicine, Afffliated Third People's Hospital, Fujian University of Traditional Chinese Medicine, Fuzhou, 350122, China; Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Xiangyang, Hubei, PR China; Institute of Neuroscience and Brain Diseases, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, PR China
| | - Fei Wang
- Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, PR China; Functional Brain Imaging Institute of Nanjing Medical University, Nanjing, PR China; Department of Mental Health, School of Public Health, Nanjing Medical University, Nanjing, PR China.
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Tandberg AD, Dahl A, Norbom LB, Westlye LT, Ystrom E, Tamnes CK, Eilertsen EM. Individual differences in internalizing symptoms in late childhood: A variance decomposition into cortical thickness, genetic and environmental differences. Dev Sci 2024:e13537. [PMID: 38874007 DOI: 10.1111/desc.13537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 03/29/2024] [Accepted: 05/24/2024] [Indexed: 06/15/2024]
Abstract
The brain undergoes extensive development during late childhood and early adolescence. Cortical thinning is a prominent feature of this development, and some researchers have suggested that differences in cortical thickness may be related to internalizing symptoms, which typically increase during the same period. However, research has yielded inconclusive results. We utilized a new method that estimates the combined effect of individual differences in vertex-wise cortical thickness on internalizing symptoms. This approach allows for many small effects to be distributed across the cortex and avoids the necessity of correcting for multiple tests. Using a sample of 8763 children aged 8.9 to 11.1 from the ABCD study, we decomposed the total variation in caregiver-reported internalizing symptoms into differences in cortical thickness, additive genetics, and shared family environmental factors and unique environmental factors. Our results indicated that individual differences in cortical thickness accounted for less than 0.5% of the variation in internalizing symptoms. In contrast, the analysis revealed a substantial effect of additive genetics and family environmental factors on the different components of internalizing symptoms, ranging from 06% to 48% and from 0% to 34%, respectively. Overall, while this study found a minimal association between cortical thickness and internalizing symptoms, additive genetics, and familial environmental factors appear to be of importance for describing differences in internalizing symptoms in late childhood. RESEARCH HIGHLIGHTS: We utilized a new method for modelling the total contribution of vertex-wise individual differences in cortical thickness to internalizing symptoms in late childhood. The total contribution of individual differences in cortical thickness accounted for <0.5% of the variance in internalizing symptoms. Additive genetics and shared family environmental variation accounted for 17% and 34% of the variance in internalizing symptoms, respectively. Our results suggest that cortical thickness is not an important indicator for internalizing symptoms in childhood, whereas genetic and environmental differences have a substantial impact.
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Affiliation(s)
- Anneli D Tandberg
- Department of Psychology, PROMENTA Research Center, University of Oslo, Oslo, Norway
| | - Andreas Dahl
- Department of Psychology, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Center for Precision Psychiatry, Oslo University Hospital, Oslo, Norway
| | - Linn B Norbom
- Department of Psychology, PROMENTA Research Center, University of Oslo, Oslo, Norway
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Center for Precision Psychiatry, Oslo University Hospital, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Eivind Ystrom
- Department of Psychology, PROMENTA Research Center, University of Oslo, Oslo, Norway
- PsychGen Centre for Genetic Epidemiology and Mental Health, Child Health and Development, Norwegian Institute of Public Health, Oslo, Norway
| | - Christian K Tamnes
- Department of Psychology, PROMENTA Research Center, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Espen M Eilertsen
- Department of Psychology, PROMENTA Research Center, University of Oslo, Oslo, Norway
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Holland CM, Alleyne K, Pierre-Louis A, Bansal R, Pollatou A, Barbato K, Cheng B, Hao X, Rosen TS, Peterson BS, Spann MN. Utilizing maternal prenatal cognition as a predictor of newborn brain measures of intellectual development. Child Neuropsychol 2024; 30:582-601. [PMID: 37489806 PMCID: PMC10808270 DOI: 10.1080/09297049.2023.2233155] [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: 03/18/2022] [Accepted: 06/28/2023] [Indexed: 07/26/2023]
Abstract
Identifying reliable indicators of cognitive functioning prior to age five has been challenging. Prior studies have shown that maternal cognition, as indexed by intellectual quotient (IQ) and years of education, predict child intelligence at school age. We examined whether maternal full scale IQ, education, and inhibitory control (index of executive function) are associated with newborn brain measures and toddler language outcomes to assess potential indicators of early cognition. We hypothesized that maternal indices of cognition would be associated with brain areas implicated in intelligence in school-age children and adults in the newborn period. Thirty-seven pregnant women and their newborns underwent an MRI scan. T2-weighted images and surface-based morphometric analysis were used to compute local brain volumes in newborn infants. Maternal cognition indices were associated with local brain volumes for infants in the anterior and posterior cingulate, occipital lobe, and pre/postcentral gyrus - regions associated with IQ, executive function, or sensori-motor functions in children and adults. Maternal education and executive function, but not maternal intelligence, were associated with toddler language scores at 12 and 24 months. Newborn brain volumes did not predict language scores. Overall, the pre/postcentral gyrus and occipital lobe may be unique indicators of early intellectual development in the newborn period. Given that maternal executive function as measured by inhibitory control has robust associations with the newborn brain and is objective, brief, and easy to administer, it may be a useful predictor of early developmental and cognitive capacity for young children.
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Affiliation(s)
- Cristin M. Holland
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY
| | - Kiarra Alleyne
- Department of Sociomedical Sciences, Columbia University Mailman School of Public Health, New York, NY
| | - Arline Pierre-Louis
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY
| | - Ravi Bansal
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA
- Department of Psychiatry, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - Angeliki Pollatou
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY
| | - Kristiana Barbato
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY
| | - Bin Cheng
- Columbia University Mailman School of Public Health, New York, NY
| | - Xuejun Hao
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY
| | - Tove S Rosen
- Columbia University Mailman School of Public Health, New York, NY
| | - Bradley S. Peterson
- Institute for the Developing Mind, Children’s Hospital Los Angeles, Los Angeles, CA
- Department of Psychiatry, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - Marisa N. Spann
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY
- New York State Psychiatric Institute, New York, NY
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Busch EL, Rapuano KM, Anderson KM, Rosenberg MD, Watts R, Casey BJ, Haxby JV, Feilong M. Dissociation of Reliability, Heritability, and Predictivity in Coarse- and Fine-Scale Functional Connectomes during Development. J Neurosci 2024; 44:e0735232023. [PMID: 38148152 PMCID: PMC10866091 DOI: 10.1523/jneurosci.0735-23.2023] [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: 03/14/2023] [Revised: 10/09/2023] [Accepted: 11/16/2023] [Indexed: 12/28/2023] Open
Abstract
The functional connectome supports information transmission through the brain at various spatial scales, from exchange between broad cortical regions to finer-scale, vertex-wise connections that underlie specific information processing mechanisms. In adults, while both the coarse- and fine-scale functional connectomes predict cognition, the fine scale can predict up to twice the variance as the coarse-scale functional connectome. Yet, past brain-wide association studies, particularly using large developmental samples, focus on the coarse connectome to understand the neural underpinnings of individual differences in cognition. Using a large cohort of children (age 9-10 years; n = 1,115 individuals; both sexes; 50% female, including 170 monozygotic and 219 dizygotic twin pairs and 337 unrelated individuals), we examine the reliability, heritability, and behavioral relevance of resting-state functional connectivity computed at different spatial scales. We use connectivity hyperalignment to improve access to reliable fine-scale (vertex-wise) connectivity information and compare the fine-scale connectome with the traditional parcel-wise (coarse scale) functional connectomes. Though individual differences in the fine-scale connectome are more reliable than those in the coarse-scale, they are less heritable. Further, the alignment and scale of connectomes influence their ability to predict behavior, whereby some cognitive traits are equally well predicted by both connectome scales, but other, less heritable cognitive traits are better predicted by the fine-scale connectome. Together, our findings suggest there are dissociable individual differences in information processing represented at different scales of the functional connectome which, in turn, have distinct implications for heritability and cognition.
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Affiliation(s)
- Erica L Busch
- Department of Psychology, Yale University, New Haven, Connecticut, 06510
| | - Kristina M Rapuano
- Department of Psychology, Yale University, New Haven, Connecticut, 06510
| | - Kevin M Anderson
- Department of Psychology, Yale University, New Haven, Connecticut, 06510
| | - Monica D Rosenberg
- Department of Psychology, University of Chicago, Chicago, Illinois, 60637
| | - Richard Watts
- Department of Psychology, Yale University, New Haven, Connecticut, 06510
| | - B J Casey
- Department of Psychology, Yale University, New Haven, Connecticut, 06510
| | - James V Haxby
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, 03755
| | - Ma Feilong
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, 03755
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Pulli EP, Nolvi S, Eskola E, Nordenswan E, Holmberg E, Copeland A, Kumpulainen V, Silver E, Merisaari H, Saunavaara J, Parkkola R, Lähdesmäki T, Saukko E, Kataja E, Korja R, Karlsson L, Karlsson H, Tuulari JJ. Structural brain correlates of non-verbal cognitive ability in 5-year-old children: Findings from the FinnBrain birth cohort study. Hum Brain Mapp 2023; 44:5582-5601. [PMID: 37606608 PMCID: PMC10619410 DOI: 10.1002/hbm.26463] [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: 03/28/2023] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 08/23/2023] Open
Abstract
Non-verbal cognitive ability predicts multiple important life outcomes, for example, school and job performance. It has been associated with parieto-frontal cortical anatomy in prior studies in adult and adolescent populations, while young children have received relatively little attention. We explored the associations between cortical anatomy and non-verbal cognitive ability in 165 5-year-old participants (mean scan age 5.40 years, SD 0.13; 90 males) from the FinnBrain Birth Cohort study. T1-weighted brain magnetic resonance images were processed using FreeSurfer. Non-verbal cognitive ability was measured using the Performance Intelligence Quotient (PIQ) estimated from the Block Design and Matrix Reasoning subtests from the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III). In vertex-wise general linear models, PIQ scores associated positively with volumes in the left caudal middle frontal and right pericalcarine regions, as well as surface area in left the caudal middle frontal, left inferior temporal, and right lingual regions. There were no associations between PIQ and cortical thickness. To the best of our knowledge, this is the first study to examine structural correlates of non-verbal cognitive ability in a large sample of typically developing 5-year-olds. The findings are generally in line with prior findings from older age groups, with the important addition of the positive association between volume / surface area in the right medial occipital region and non-verbal cognitive ability. This finding adds to the literature by discovering a new brain region that should be considered in future studies exploring the role of cortical structure for cognitive development in young children.
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Affiliation(s)
- Elmo P. Pulli
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Saara Nolvi
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Turku Institute for Advanced Studies, Department of Psychology and Speech‐Language PathologyUniversity of TurkuTurkuFinland
| | - Eeva Eskola
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of PsychologyUniversity of TurkuTurkuFinland
| | - Elisabeth Nordenswan
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Eeva Holmberg
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Anni Copeland
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Venla Kumpulainen
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Eero Silver
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Harri Merisaari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of RadiologyUniversity of TurkuTurkuFinland
| | - Jani Saunavaara
- Department of Medical PhysicsTurku University Hospital and University of TurkuTurkuFinland
| | - Riitta Parkkola
- Department of RadiologyUniversity of TurkuTurkuFinland
- Department of RadiologyTurku University HospitalTurkuFinland
| | - Tuire Lähdesmäki
- Pediatric Neurology, Department of Pediatrics and Adolescent MedicineTurku University Hospital and University of TurkuTurkuFinland
| | | | - Eeva‐Leena Kataja
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
| | - Riikka Korja
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of PsychologyUniversity of TurkuTurkuFinland
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of Pediatrics and Adolescent MedicineTurku University Hospital and University of TurkuTurkuFinland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of PsychiatryTurku University Hospital and University of TurkuTurkuFinland
| | - Jetro J. Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical MedicineUniversity of TurkuTurkuFinland
- Centre for Population Health ResearchTurku University Hospital and University of TurkuTurkuFinland
- Department of PsychiatryTurku University Hospital and University of TurkuTurkuFinland
- Turku Collegium for Science, Medicine and TechnologyUniversity of TurkuTurkuFinland
- Department of PsychiatryUniversity of OxfordOxfordUK
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Etami Y, Lildharrie C, Manza P, Wang GJ, Volkow ND. Neuroimaging in Adolescents: Post-Traumatic Stress Disorder and Risk for Substance Use Disorders. Genes (Basel) 2023; 14:2113. [PMID: 38136935 PMCID: PMC10743116 DOI: 10.3390/genes14122113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Revised: 11/17/2023] [Accepted: 11/21/2023] [Indexed: 12/24/2023] Open
Abstract
Trauma in childhood and adolescence has long-term negative consequences in brain development and behavior and increases the risk for psychiatric disorders. Among them, post-traumatic stress disorder (PTSD) during adolescence illustrates the connection between trauma and substance misuse, as adolescents may utilize substances to cope with PTSD. Drug misuse may in turn lead to neuroadaptations in learning processes that facilitate the consolidation of traumatic memories that perpetuate PTSD. This reflects, apart from common genetic and epigenetic modifications, overlapping neurocircuitry engagement triggered by stress and drug misuse that includes structural and functional changes in limbic brain regions and the salience, default-mode, and frontoparietal networks. Effective strategies to prevent PTSD are needed to limit the negative consequences associated with the later development of a substance use disorder (SUD). In this review, we will examine the link between PTSD and SUDs, along with the resulting effects on memory, focusing on the connection between the development of an SUD in individuals who struggled with PTSD in adolescence. Neuroimaging has emerged as a powerful tool to provide insight into the brain mechanisms underlying the connection of PTSD in adolescence and the development of SUDs.
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Affiliation(s)
| | | | | | - Gene-Jack Wang
- Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD 20892, USA; (Y.E.); (C.L.); (P.M.); (N.D.V.)
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8
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Hao L, Fan Y, Zhang X, Rong X, Sun Y, Liu K. Functional physical training improves fitness and cognitive development in 4~5 years old children. Front Psychol 2023; 14:1266216. [PMID: 38034291 PMCID: PMC10684932 DOI: 10.3389/fpsyg.2023.1266216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 10/23/2023] [Indexed: 12/02/2023] Open
Abstract
Background Development of physical and cognitive function is very critical in 4~5 years children. It has been addressed in this research if the 18 weeks of specific functional training with or without cognitive training can be effective on improving fitness and cognitive development in 4~5 years preschool children. Methods A total of 126 preschool children in the 4~5 age range were selected as participants and randomly assigned to one of four groups: the control group (C), the functional physical training group (P), the cognitive training group (CT), and the functional physical training combined with cognitive training group (PCT). Results The results revealed significant pre/post differences in body height and weight among all four groups of children. Furthermore, there was no significant difference in physical fitness between the C group and the CT group after the intervention. However, the children in the P group and the PCT group showed significant improvements in three indicators including standing long jump, continuous jump, and 10-meter shuttle running. Additionally, the children in P group, CT group, and the PCT group demonstrated significant improvement in simple reaction time, attention, and spatial memory. No significant cognitive improvement was found in C group. Conclusion Functional physical training with or without cognitive intervention can promote both physical fitness and cognitive development in children aged 4~5 years. Cognitive training alone can significantly improve cognitive function but not physical. Therefore, functional physical training can be used alone to improve the physical and cognitive abilities for aged 4~5 years old children.
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Affiliation(s)
- Lei Hao
- College of Physical Education and Health, East China Normal University, Shanghai, China
| | - Yongzhao Fan
- Department of Physical Education, Henan Normal University, Xinxiang, Henan, China
| | - Xiaojuan Zhang
- Graduate School, Capital University of Physical Education and Sports, Beijing, China
| | - Xiangjiang Rong
- Graduate School, Capital University of Physical Education and Sports, Beijing, China
| | - Youping Sun
- College of Physical Education and Health, East China Normal University, Shanghai, China
| | - Kun Liu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
- Brain Peace Science Foundation, New Haven, CT, United States
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Morey R, Zheng Y, Sun D, Garrett M, Gasperi M, Maihofer A, Baird CL, Grasby K, Huggins A, Haswell C, Thompson P, Medland S, Gustavson D, Panizzon M, Kremen W, Nievergelt C, Ashley-Koch A, Logue L. Genomic Structural Equation Modeling Reveals Latent Phenotypes in the Human Cortex with Distinct Genetic Architecture. RESEARCH SQUARE 2023:rs.3.rs-3253035. [PMID: 37886496 PMCID: PMC10602057 DOI: 10.21203/rs.3.rs-3253035/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to map the genetic architecture of cortical surface area (SA) and cortical thickness (CT) for the 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance, which we are denoting genetically informed brain networks (GIBNs). Genomic SEM can fit a multivariate GWAS from summary statistics for each of the GIBNs, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA identified 6 GIBNs and CT identified 4 GIBNs. The multivariate GWASs of these GIBNs identified 74 genome-wide significant (GWS) loci (p<5×10-8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of GIBN GWASs found that SA-derived GIBNs had a positive genetic correlation with bipolar disorder (BPD), and cannabis use disorder, indicating genetic predisposition to a larger SA in the specific GIBN is associated with greater genetic risk of these disorders. A negative genetic correlation was observed with attention deficit hyperactivity disorder (ADHD), major depressive disorder (MDD), and insomnia, indicating genetic predisposition to a larger SA in the specific GIBN is associated with lower genetic risk of these disorders. CT GIBNs displayed a negative genetic correlation with alcohol dependence. Jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across phenotypes offers a new vantage point for mapping the cortex into genetically informed networks.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Paul Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of the University of Southern California, Marina del Rey, California, USA
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10
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He Q, Keding TJ, Zhang Q, Miao J, Russell JD, Herringa RJ, Lu Q, Travers BG, Li JJ. Neurogenetic mechanisms of risk for ADHD: Examining associations of polygenic scores and brain volumes in a population cohort. J Neurodev Disord 2023; 15:30. [PMID: 37653373 PMCID: PMC10469494 DOI: 10.1186/s11689-023-09498-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 08/21/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND ADHD polygenic scores (PGSs) have been previously shown to predict ADHD outcomes in several studies. However, ADHD PGSs are typically correlated with ADHD but not necessarily reflective of causal mechanisms. More research is needed to elucidate the neurobiological mechanisms underlying ADHD. We leveraged functional annotation information into an ADHD PGS to (1) improve the prediction performance over a non-annotated ADHD PGS and (2) test whether volumetric variation in brain regions putatively associated with ADHD mediate the association between PGSs and ADHD outcomes. METHODS Data were from the Philadelphia Neurodevelopmental Cohort (N = 555). Multiple mediation models were tested to examine the indirect effects of two ADHD PGSs-one using a traditional computation involving clumping and thresholding and another using a functionally annotated approach (i.e., AnnoPred)-on ADHD inattention (IA) and hyperactivity-impulsivity (HI) symptoms, via gray matter volumes in the cingulate gyrus, angular gyrus, caudate, dorsolateral prefrontal cortex (DLPFC), and inferior temporal lobe. RESULTS A direct effect was detected between the AnnoPred ADHD PGS and IA symptoms in adolescents. No indirect effects via brain volumes were detected for either IA or HI symptoms. However, both ADHD PGSs were negatively associated with the DLPFC. CONCLUSIONS The AnnoPred ADHD PGS was a more developmentally specific predictor of adolescent IA symptoms compared to the traditional ADHD PGS. However, brain volumes did not mediate the effects of either a traditional or AnnoPred ADHD PGS on ADHD symptoms, suggesting that we may still be underpowered in clarifying brain-based biomarkers for ADHD using genetic measures.
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Affiliation(s)
- Quanfa He
- Department of Psychology, University of, Wisconsin-Madison, 1202 W. Johnson Street, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, USA
| | | | - Qi Zhang
- Department of Educational Psychology, University of Wisconsin-Madison, Madison, USA
| | - Jiacheng Miao
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, USA
| | - Justin D Russell
- Department of Psychiatry, School of Medicine and Public Health, University of Wisconsin, Madison, USA
| | - Ryan J Herringa
- Department of Psychiatry, School of Medicine and Public Health, University of Wisconsin, Madison, USA
| | - Qiongshi Lu
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, USA
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, USA
- Department of Statistics, University of Wisconsin-Madison, Madison, USA
| | - Brittany G Travers
- Waisman Center, University of Wisconsin-Madison, Madison, USA
- Department of Kinesiology, University of Wisconsin-Madison, Madison, USA
| | - James J Li
- Department of Psychology, University of, Wisconsin-Madison, 1202 W. Johnson Street, Madison, WI, 53706, USA.
- Waisman Center, University of Wisconsin-Madison, Madison, USA.
- Center for Demography of Health and Aging, University of Wisconsin-Madison, Madison, USA.
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11
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Bibollet-Bahena O, Tissier S, Ho-Tran S, Rojewski A, Casanova C. Enriched environment exposure during development positively impacts the structure and function of the visual cortex in mice. Sci Rep 2023; 13:7020. [PMID: 37120630 PMCID: PMC10148800 DOI: 10.1038/s41598-023-33951-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 04/21/2023] [Indexed: 05/01/2023] Open
Abstract
Optimal conditions of development have been of interest for decades, since genetics alone cannot fully explain how an individual matures. In the present study, we used optical brain imaging to investigate whether a relatively simple enrichment can positively influence the development of the visual cortex of mice. The enrichment paradigm was composed of larger cages housing multiple mice that contained several toys, hiding places, nesting material and a spinning wheel that were moved or replaced at regular intervals. We compared C57BL/6N adult mice (> P60) that had been raised either in an enriched environment (EE; n = 16) or a standard (ST; n = 12) environment from 1 week before birth to adulthood, encompassing all cortical developmental stages. Here, we report significant beneficial changes on the structure and function of the visual cortex following environmental enrichment throughout the lifespan. More specifically, retinotopic mapping through intrinsic signal optical imaging revealed that the size of the primary visual cortex was greater in mice reared in an EE compared to controls. In addition, the visual field coverage of EE mice was wider. Finally, the organization of the cortical representation of the visual field (as determined by cortical magnification) versus its eccentricity also differed between the two groups. We did not observe any significant differences between females and males within each group. Taken together, these data demonstrate specific benefits of an EE throughout development on the visual cortex, which suggests adaptation to their environmental realities.
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Affiliation(s)
- O Bibollet-Bahena
- Laboratoire des Neurosciences de la Vision, School of Optometry, Université de Montréal, Montreal, QC, Canada.
| | - S Tissier
- Laboratoire des Neurosciences de la Vision, School of Optometry, Université de Montréal, Montreal, QC, Canada
| | - S Ho-Tran
- Laboratoire des Neurosciences de la Vision, School of Optometry, Université de Montréal, Montreal, QC, Canada
| | - A Rojewski
- Laboratoire des Neurosciences de la Vision, School of Optometry, Université de Montréal, Montreal, QC, Canada
| | - C Casanova
- Laboratoire des Neurosciences de la Vision, School of Optometry, Université de Montréal, Montreal, QC, Canada
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12
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Environmental effects on brain functional networks in a juvenile twin population. Sci Rep 2023; 13:3921. [PMID: 36894644 PMCID: PMC9998648 DOI: 10.1038/s41598-023-30672-2] [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: 09/08/2022] [Accepted: 02/28/2023] [Indexed: 03/11/2023] Open
Abstract
The brain's intrinsic organization into large-scale functional networks, the resting state networks (RSN), shows complex inter-individual variability, consolidated during development. Nevertheless, the role of gene and environment on developmental brain functional connectivity (FC) remains largely unknown. Twin design represents an optimal platform to shed light on these effects acting on RSN characteristics. In this study, we applied statistical twin methods to resting-state functional magnetic resonance imaging (rs-fMRI) scans from 50 young twin pairs (aged 10-30 years) to preliminarily explore developmental determinants of brain FC. Multi-scale FC features were extracted and tested for applicability of classical ACE and ADE twin designs. Epistatic genetic effects were also assessed. In our sample, genetic and environmental effects on the brain functional connections largely varied between brain regions and FC features, showing good consistency at multiple spatial scales. Although we found selective contributions of common environment on temporo-occipital connections and of genetics on frontotemporal connections, the unique environment showed a predominant effect on FC link- and node-level features. Despite the lack of accurate genetic modeling, our preliminary results showed complex relationships between genes, environment, and functional brain connections during development. A predominant role of the unique environment on multi-scale RSN characteristics was suggested, which needs replications on independent samples. Future investigations should especially focus on nonadditive genetic effects, which remain largely unexplored.
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13
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Wang C, Sanvito F, Oughourlian TC, Islam S, Salamon N, Holly LT, Ellingson BM. Structural Relationship between Cerebral Gray and White Matter Alterations in Degenerative Cervical Myelopathy. Tomography 2023; 9:315-327. [PMID: 36828377 PMCID: PMC9961386 DOI: 10.3390/tomography9010025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 01/23/2023] [Accepted: 01/29/2023] [Indexed: 02/04/2023] Open
Abstract
Patients with degenerative cervical myelopathy (DCM) undergo adaptive supraspinal changes. However, it remains unknown how subcortical white matter changes reflect the gray matter loss. The current study investigated the interrelationship between gray matter and subcortical white matter alterations in DCM patients. Cortical thickness of gray matter, as well as the intra-cellular volume fraction (ICVF) of subcortical whiter matter, were assessed in a cohort of 44 patients and 17 healthy controls (HCs). The results demonstrated that cortical thinning of sensorimotor and pain related regions is associated with more severe DCM symptoms. ICVF values of subcortical white matter underlying the identified regions were significantly lower in study patients than in HCs. The left precentral gyrus (r = 0.5715, p < 0.0001), the left supramarginal gyrus (r = 0.3847, p = 0.0099), the left postcentral gyrus (r = 0.5195, p = 0.0003), the right superior frontal gyrus (r = 0.3266, p = 0.0305), and the right caudal (r = 0.4749, p = 0.0011) and rostral anterior cingulate (r = 0.3927, p = 0.0084) demonstrated positive correlations between ICVF and cortical thickness in study patients, but no significant correlations between ICVF and cortical thickness were observed in HCs. Results from the current study suggest that DCM may cause widespread gray matter alterations and underlying subcortical neurite loss, which may serve as potential imaging biomarkers reflecting the pathology of DCM.
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Affiliation(s)
- Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA
| | - Francesco Sanvito
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA
- Unit of Radiology, Department of Clinical, Surgical, Diagnostic, and Pediatric Sciences, University of Pavia, 27100 Pavia, Italy
| | - Talia C. Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA
- Neuroscience Interdepartmental Graduate Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA
| | - Sabah Islam
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA
| | - Langston T. Holly
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA
| | - Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA
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14
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Maes HHM, Lapato DM, Schmitt JE, Luciana M, Banich MT, Bjork JM, Hewitt JK, Madden PA, Heath AC, Barch DM, Thompson WK, Iacono WG, Neale MC. Genetic and Environmental Variation in Continuous Phenotypes in the ABCD Study®. Behav Genet 2023; 53:1-24. [PMID: 36357558 PMCID: PMC9823057 DOI: 10.1007/s10519-022-10123-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Accepted: 10/11/2022] [Indexed: 11/12/2022]
Abstract
Twin studies yield valuable insights into the sources of variation, covariation and causation in human traits. The ABCD Study® (abcdstudy.org) was designed to take advantage of four universities known for their twin research, neuroimaging, population-based sampling, and expertise in genetic epidemiology so that representative twin studies could be performed. In this paper we use the twin data to: (i) provide initial estimates of heritability for the wide range of phenotypes assessed in the ABCD Study using a consistent direct variance estimation approach, assuring that both data and methodology are sound; and (ii) provide an online resource for researchers that can serve as a reference point for future behavior genetic studies of this publicly available dataset. Data were analyzed from 772 pairs of twins aged 9-10 years at study inception, with zygosity determined using genotypic data, recruited and assessed at four twin hub sites. The online tool provides twin correlations and both standardized and unstandardized estimates of additive genetic, and environmental variation for 14,500 continuously distributed phenotypic features, including: structural and functional neuroimaging, neurocognition, personality, psychopathology, substance use propensity, physical, and environmental trait variables. The estimates were obtained using an unconstrained variance approach, so they can be incorporated directly into meta-analyses without upwardly biasing aggregate estimates. The results indicated broad consistency with prior literature where available and provided novel estimates for phenotypes without prior twin studies or those assessed at different ages. Effects of site, self-identified race/ethnicity, age and sex were statistically controlled. Results from genetic modeling of all 53,172 continuous variables, including 38,672 functional MRI variables, will be accessible via the user-friendly open-access web interface we have established, and will be updated as new data are released from the ABCD Study. This paper provides an overview of the initial results from the twin study embedded within the ABCD Study, an introduction to the primary research domains in the ABCD study and twin methodology, and an evaluation of the initial findings with a focus on data quality and suitability for future behavior genetic studies using the ABCD dataset. The broad introductory material is provided in recognition of the multidisciplinary appeal of the ABCD Study. While this paper focuses on univariate analyses, we emphasize the opportunities for multivariate, developmental and causal analyses, as well as those evaluating heterogeneity by key moderators such as sex, demographic factors and genetic background.
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Affiliation(s)
- Hermine H. M. Maes
- grid.224260.00000 0004 0458 8737Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980033, Richmond, VA 23298-0033 USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA ,grid.224260.00000 0004 0458 8737Massey Cancer Center, Virginia Commonwealth University, Richmond, VA USA
| | - Dana M. Lapato
- grid.224260.00000 0004 0458 8737Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980033, Richmond, VA 23298-0033 USA
| | - J. Eric Schmitt
- grid.25879.310000 0004 1936 8972Departments of Radiology and Psychiatry, University of Pennsylvania, Philadelphia, PA USA
| | - Monica Luciana
- grid.17635.360000000419368657Department of Psychology, University of Minnesota, Minneapolis, USA
| | - Marie T. Banich
- grid.266190.a0000000096214564Department of Psychology and Neuroscience, University of Colorado, Boulder, USA ,grid.266190.a0000000096214564Institute of Cognitive Science, University of Colorado, Boulder, USA
| | - James M. Bjork
- grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA
| | - John K. Hewitt
- grid.266190.a0000000096214564Institute of Cognitive Science, University of Colorado, Boulder, USA ,grid.266190.a0000000096214564Institute for Behavioral Genetics, University of Colorado, Boulder, USA
| | - Pamela A. Madden
- grid.4367.60000 0001 2355 7002Department of Psychiatry, Washington University in St Louis, St Louis, MO USA
| | - Andrew C. Heath
- grid.4367.60000 0001 2355 7002Department of Psychiatry, Washington University in St Louis, St Louis, MO USA
| | - Deanna M. Barch
- grid.4367.60000 0001 2355 7002Department of Psychiatry, Washington University in St Louis, St Louis, MO USA
| | - Wes K. Thompson
- grid.266100.30000 0001 2107 4242Division of Biostatistics and Department of Radiology, Population Neuroscience and Genetics Lab, University of California at San Diego, La Jolla, CA USA
| | - William G. Iacono
- grid.17635.360000000419368657Department of Psychology, University of Minnesota, Minneapolis, USA
| | - Michael C. Neale
- grid.224260.00000 0004 0458 8737Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980033, Richmond, VA 23298-0033 USA ,grid.224260.00000 0004 0458 8737Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA USA
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15
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Associations between brain imaging and polygenic scores of mental health and educational attainment in children aged 9-11. Neuroimage 2022; 263:119611. [PMID: 36070838 DOI: 10.1016/j.neuroimage.2022.119611] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 08/03/2022] [Accepted: 09/03/2022] [Indexed: 12/25/2022] Open
Abstract
Psychiatric disorders are highly heritable and polygenic, and many have their peak onset in late childhood and adolescence, a period of tremendous changes. Although the neurodevelopmental antecedents of mental illness are widely acknowledged, research in youth population cohorts is still scarce, preventing our progress towards the early characterization of these disorders. We included 7,124 children (9-11 years old) from the Adolescent Brain and Cognitive Development Study to map the associations of structural and diffusion brain imaging with common genetic variants and polygenic scores for psychiatric disorders and educational attainment. We used principal component analysis to derive imaging components, and calculated their heritability. We then assessed the relationship of imaging components with genetic and clinical psychiatric risk with univariate models and Canonical correlation analysis (CCA). Most imaging components had moderate heritability. Univariate models showed limited evidence and small associations of polygenic scores with brain structure at this age. CCA revealed two significant modes of covariation. The first mode linked higher polygenic scores for educational attainment with less externalizing problems and larger surface area. The second mode related higher polygenic scores for schizophrenia, bipolar disorder, and autism spectrum disorder to higher global cortical thickness, smaller white matter volumes of the fornix and cingulum, larger medial occipital surface area and smaller surface area of lateral and medial temporal regions. While cross-validation suggested limited generalizability, our results highlight the potential of multivariate models to better understand the transdiagnostic and distributed relationships between mental health and brain structure in late childhood.
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16
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Troiani V, Snyder W, Kozick S, Patti MA, Beiler D. Variability and concordance of sulcal patterns in the orbitofrontal cortex: A twin study. Psychiatry Res Neuroimaging 2022; 324:111492. [PMID: 35597228 DOI: 10.1016/j.pscychresns.2022.111492] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 03/15/2022] [Accepted: 05/13/2022] [Indexed: 10/18/2022]
Abstract
Sulcogyral patterns have been identified in the orbitofrontal cortex (OFC) based on the continuity of the medial and lateral orbital sulci. Pattern types are named according to their frequency in the population, with Type I present in ∼60%, Type II in ∼25%, Type III in ∼10%, and Type IV in ∼5%. Previous work has demonstrated that psychiatric conditions with high estimated heritability (e.g. schizophrenia, bipolar disorder) are associated with reduced frequency of Type I patterns, but the general heritability of the OFC sulcogyral patterns is unknown. We examined concordance of OFC patterns in 304 monozygotic (MZ) twins relative to 172 dizygotic (DZ) twins using structural magnetic resonance imaging data. We find that the frequency of pattern types within MZ and DZ twins are similar and bilateral concordance rates across all pattern types in DZ twins were 14% and 21% for MZ twins. Results from follow-up analyses confirm that continuity in the rostral-caudal direction is an important source of variability within the OFC, and subtype analyses indicate that variability is present in other sulci that are not represented by overall OFC pattern type. Overall, these results suggest that OFC sulcogyral patterns may reflect important variance that is not genetic in origin.
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Affiliation(s)
- Vanessa Troiani
- Geisinger Autism and Developmental Medicine Institute, 120 Hamm Drive, Suite 2A, Lewisburg, PA 17837, United States.
| | - Will Snyder
- Geisinger Autism and Developmental Medicine Institute, 120 Hamm Drive, Suite 2A, Lewisburg, PA 17837, United States
| | - Shane Kozick
- Geisinger Autism and Developmental Medicine Institute, 120 Hamm Drive, Suite 2A, Lewisburg, PA 17837, United States
| | - Marisa A Patti
- Geisinger Autism and Developmental Medicine Institute, 120 Hamm Drive, Suite 2A, Lewisburg, PA 17837, United States
| | - Donielle Beiler
- Geisinger Autism and Developmental Medicine Institute, 120 Hamm Drive, Suite 2A, Lewisburg, PA 17837, United States
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17
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Dimick MK, Kennedy KG, Mitchell RHB, Sinyor M, MacIntosh BJ, Goldstein BI. Neurostructural differences associated with self-harm in youth bipolar disorder. Bipolar Disord 2022; 24:275-285. [PMID: 34596314 DOI: 10.1111/bdi.13137] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 08/19/2021] [Accepted: 09/25/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND Youth with bipolar disorder (BD) are at greatly elevated risk for suicide. Self-harm, encompassing all self-injurious behaviors regardless of suicidal intent, is among one of the greatest risk factors for death by suicide. This study aims to extend the sparse literature regarding the neurostructural correlates of self-harm in youth with BD. METHODS Participants included 156 youth (17.14 ± 1.61 years): 38 BD with lifetime history of self-harm (BDSH+ ), 43 BD without history of self-harm (BDSH- ), and 75 healthy controls (HC). Measures of cortical thickness, surface area (SA), and volume were obtained using 3 T magnetic resonance imaging. Orbitofrontal and ventrolateral prefrontal cortices were examined in region-of-interest (ROI) analyses, complemented by exploratory vertex-wise analyses using a general linear model controlling for age, sex, and intracranial volume. RESULTS In ROI analyses, there were no between-group differences after correction for multiple comparisons. Vertex-wise analysis revealed three significant clusters in precentral gyrus SA, inferior temporal gyrus SA, and caudal middle frontal gyrus volume. Post-hoc vertex-wise analyses showed BDSH+ had lower cortical SA and volume compared with both BDSH- and HC for all clusters. CONCLUSIONS Significant vertex-wise findings were observed in frontotemporal regions relevant to BD and self-harm, with smaller neurostructural measures among BDSH+ compared with both BDSH- and HC. Future studies are needed to evaluate the temporal nature of the relationship of these neurostructural differences (i.e., potential risk indicators) to self-harm and to identify mechanisms underlying these findings.
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Affiliation(s)
- Mikaela K Dimick
- Centre for Youth Bipolar Disorder, Child and Youth Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Pharmacology and Toxicology, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada
| | - Kody G Kennedy
- Centre for Youth Bipolar Disorder, Child and Youth Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Pharmacology and Toxicology, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada
| | - Rachel H B Mitchell
- Department of Psychiatry, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada.,Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Mark Sinyor
- Department of Psychiatry, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada.,Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Bradley J MacIntosh
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Hurvitz Brain Sciences, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Benjamin I Goldstein
- Centre for Youth Bipolar Disorder, Child and Youth Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Pharmacology and Toxicology, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto Faculty of Medicine, Toronto, Ontario, Canada.,Department of Psychiatry, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
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18
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A Review of Family Environment and Neurobehavioral Outcomes Following Pediatric Traumatic Brain Injury: Implications of Early Adverse Experiences, Family Stress, and Limbic Development. Biol Psychiatry 2022; 91:488-497. [PMID: 34772505 DOI: 10.1016/j.biopsych.2021.08.012] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 07/21/2021] [Accepted: 08/11/2021] [Indexed: 12/30/2022]
Abstract
Pediatric traumatic brain injury (TBI) is a public health crisis, with neurobehavioral morbidity observed years after an injury associated with changes in related brain structures. A substantial literature base has established family environment as a significant predictor of neurobehavioral outcomes following pediatric TBI. The neural mechanisms linking family environment to neurobehavioral outcomes have, however, received less empiric study in this population. In contrast, limbic structural differences as well as challenges with emotional adjustment and behavioral regulation in non-TBI populations have been linked to a multitude of family environmental factors, including family stress, parenting style, and adverse childhood experiences. In this article, we systematically review the more comprehensive literature on family environment and neurobehavioral outcomes in pediatric TBI and leverage the work in both TBI and non-TBI populations to expand our understanding of the underlying neural mechanisms. Thus, we summarize the extant literature on the family environment's role in neurobehavioral sequelae in children with TBI and explore potential neural correlates by synthesizing the wealth of literature on family environment and limbic development, specifically related to the amygdala. This review underscores the critical role of environmental factors, especially those predating the injury, in modeling recovery outcomes post-TBI in childhood, and discusses clinical and research implications across pediatric populations. Given the public health crisis of pediatric TBI, along with the context of sparse available medical interventions, a broader understanding of factors contributing to outcomes is warranted to expand the range of intervention targets.
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Gu S, Fotiadis P, Parkes L, Xia CH, Gur RC, Gur RE, Roalf DR, Satterthwaite TD, Bassett DS. Network controllability mediates the relationship between rigid structure and flexible dynamics. Netw Neurosci 2022; 6:275-297. [PMID: 36605890 PMCID: PMC9810281 DOI: 10.1162/netn_a_00225] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 12/15/2021] [Indexed: 01/07/2023] Open
Abstract
Precisely how the anatomical structure of the brain supports a wide range of complex functions remains a question of marked importance in both basic and clinical neuroscience. Progress has been hampered by the lack of theoretical frameworks explaining how a structural network of relatively rigid interareal connections can produce a diverse repertoire of functional neural dynamics. Here, we address this gap by positing that the brain's structural network architecture determines the set of accessible functional connectivity patterns according to predictions of network control theory. In a large developmental cohort of 823 youths aged 8 to 23 years, we found that the flexibility of a brain region's functional connectivity was positively correlated with the proportion of its structural links extending to different cognitive systems. Notably, this relationship was mediated by nodes' boundary controllability, suggesting that a region's strategic location on the boundaries of modules may underpin the capacity to integrate information across different cognitive processes. Broadly, our study provides a mechanistic framework that illustrates how temporal flexibility observed in functional networks may be mediated by the controllability of the underlying structural connectivity.
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Affiliation(s)
- Shi Gu
- Brain and Intelligence Group, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Panagiotis Fotiadis
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Linden Parkes
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Cedric H. Xia
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ruben C. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Raquel E. Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David R. Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D. Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dani S. Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Santa Fe Institute, Santa Fe, NM, USA
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20
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Aberizk K, Collins MA, Addington J, Bearden CE, Cadenhead KS, Cornblatt BA, Mathalon DH, McGlashan TH, Perkins DO, Tsuang MT, Woods SW, Cannon TD, Walker EF. Life Event Stress and Reduced Cortical Thickness in Youth at Clinical High Risk for Psychosis and Healthy Control Subjects. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:171-179. [PMID: 33930604 PMCID: PMC8551305 DOI: 10.1016/j.bpsc.2021.04.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 03/21/2021] [Accepted: 04/20/2021] [Indexed: 02/03/2023]
Abstract
BACKGROUND A decline in cortical thickness during early life appears to be a normal neuromaturational process. Accelerated cortical thinning has been linked with conversion to psychosis among individuals at clinical high risk for psychosis (CHR-P). Previous research indicates that exposure to life event stress (LES) is associated with exaggerated cortical thinning in both healthy and clinical populations, and LES is also linked with conversion to psychosis in CHR-P. To date, there are no reports on the relationship of LES with cortical thickness in CHR-P. This study examines this relationship and whether LES is linked with cortical thinning to a greater degree in individuals at CHR-P who convert to psychosis compared with individuals at CHR-P who do not convert and healthy control subjects. METHODS Controlling for age and gender (364 male, 262 female), this study examined associations between LES and baseline cortical thickness in 436 individuals at CHR-P (375 nonconverters and 61 converters) and 190 comparison subjects in the North American Prodrome Longitudinal Study. RESULTS Findings indicate that prebaseline cumulative LES is associated with reduced baseline cortical thickness in several regions among the CHR-P and control groups. Evidence suggests that LES is a risk factor for thinner cortex to the same extent across diagnostic groups, while CHR-P status is linked with thinner cortex in select regions after accounting for LES. CONCLUSIONS This research provides additional evidence to support the role of LES in cortical thinning in both healthy youth and those at CHR-P. Potential underlying mechanisms of the findings and implications for future research are discussed.
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Affiliation(s)
- Katrina Aberizk
- Department of Psychology, Emory University, Atlanta, Georgia.
| | - Meghan A Collins
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Jean Addington
- Department of Psychiatry, University of Calgary, Calgary, Alberta, Canada
| | - Carrie E Bearden
- Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California; Department of Psychology, University of California Los Angeles, Los Angeles, California
| | - Kristin S Cadenhead
- Department of Psychiatry, University of California San Diego, San Diego, California
| | | | - Daniel H Mathalon
- Department of Psychiatry, University of California San Francisco, San Francisco, California; San Francisco VA Medical Center, San Francisco, California
| | | | - Diana O Perkins
- Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina
| | - Ming T Tsuang
- Department of Psychiatry, University of California San Diego, San Diego, California
| | - Scott W Woods
- Department of Psychiatry, Yale University, New Haven, Connecticut
| | - Tyrone D Cannon
- Department of Psychology, Yale University, New Haven, Connecticut; Department of Psychiatry, Yale University, New Haven, Connecticut
| | - Elaine F Walker
- Department of Psychology, Emory University, Atlanta, Georgia
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21
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Fehlbaum LV, Peters L, Dimanova P, Roell M, Borbás R, Ansari D, Raschle NM. Mother-child similarity in brain morphology: A comparison of structural characteristics of the brain's reading network. Dev Cogn Neurosci 2022; 53:101058. [PMID: 34999505 PMCID: PMC8749220 DOI: 10.1016/j.dcn.2022.101058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 11/19/2021] [Accepted: 01/03/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Substantial evidence acknowledges the complex gene-environment interplay impacting brain development and learning. Intergenerational neuroimaging allows the assessment of familial transfer effects on brain structure, function and behavior by investigating neural similarity in caregiver-child dyads. METHODS Neural similarity in the human reading network was assessed through well-used measures of brain structure (i.e., surface area (SA), gyrification (lG), sulcal morphology, gray matter volume (GMV) and cortical thickness (CT)) in 69 mother-child dyads (children's age~11 y). Regions of interest for the reading network included left-hemispheric inferior frontal gyrus, inferior parietal lobe and fusiform gyrus. Mother-child similarity was quantified by correlation coefficients and familial specificity was tested by comparison to random adult-child dyads. Sulcal morphology analyses focused on occipitotemporal sulcus interruptions and similarity was assessed by chi-square goodness of fit. RESULTS Significant structural brain similarity was observed for mother-child dyads in the reading network for lG, SA and GMV (r = 0.349/0.534/0.542, respectively), but not CT. Sulcal morphology associations were non-significant. Structural brain similarity in lG, SA and GMV were specific to mother-child pairs. Furthermore, structural brain similarity for SA and GMV was higher compared to CT. CONCLUSION Intergenerational neuroimaging techniques promise to enhance our knowledge of familial transfer effects on brain development and disorders.
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Affiliation(s)
- Lynn V Fehlbaum
- Jacobs Center for Productive Youth Development at the University of Zurich, Zurich, Switzerland
| | - Lien Peters
- Numerical Cognition Laboratory, Department of Psychology and Brain and Mind Institute, University of Western Ontario, London, Canada
| | - Plamina Dimanova
- Jacobs Center for Productive Youth Development at the University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland
| | - Margot Roell
- Parenting and Special Education Research Unit, Faculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium
| | - Réka Borbás
- Jacobs Center for Productive Youth Development at the University of Zurich, Zurich, Switzerland
| | - Daniel Ansari
- Numerical Cognition Laboratory, Department of Psychology and Brain and Mind Institute, University of Western Ontario, London, Canada
| | - Nora M Raschle
- Jacobs Center for Productive Youth Development at the University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Switzerland.
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22
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Xia K, Schmitt JE, Jha SC, Girault JB, Cornea E, Li G, Shen D, Styner M, Gilmore JH. Genetic Influences on Longitudinal Trajectories of Cortical Thickness and Surface Area during the First 2 Years of Life. Cereb Cortex 2022; 32:367-379. [PMID: 34231837 PMCID: PMC8897991 DOI: 10.1093/cercor/bhab213] [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: 01/15/2021] [Revised: 06/09/2021] [Accepted: 06/09/2021] [Indexed: 11/14/2022] Open
Abstract
Genetic influences on cortical thickness (CT) and surface area (SA) are known to vary across the life span. Little is known about the extent to which genetic factors influence CT and SA in infancy and toddlerhood. We performed the first longitudinal assessment of genetic influences on variation in CT and SA in 501 twins who were aged 0-2 years. We observed substantial additive genetic influences on both average CT (0.48 in neonates, 0.37 in 1-year-olds, and 0.44 in 2-year-olds) and total SA (0.59 in neonates, 0.74 in 1-year-olds, and 0.73 in 2-year-olds). In addition, we found strong heritability of the change in average CT (0.49) from neonates to 1-year-olds, but not from 1- to 2-year-olds. Moreover, we found strong genetic correlations for average CT (rG = 0.92) between 1- and 2-year-olds and strong genetic correlations for total SA across all timepoints (rG = 0.96 between neonates and 1-year-olds, rG = 1 between 1- and 2-year-olds). In addition, we found CT and SA are strongly genetic correlated at birth, but weaken over time. Overall, results suggest a dynamic genetic relationship between CT and SA during first 2 years of life and provide novel insights into how genetic influences shape the cortical structure during early brain development.
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Affiliation(s)
- Kai Xia
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599-7160, USA
| | - J Eric Schmitt
- Brain Behavior Laboratory, Department of Psychiatry, Neuropsychiatry Section, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shaili C Jha
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA 02115, USA
| | - Jessica B Girault
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599-7160, USA
| | - Emil Cornea
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599-7160, USA
| | - Gang Li
- Department of Radiology, University of North Carolina, Chapel Hill, NC 27599-7320, USA
| | - Dinggang Shen
- Department of Radiology, University of North Carolina, Chapel Hill, NC 27599-7320, USA
| | - Martin Styner
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599-7160, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599-7160, USA
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23
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Keil MF, Leahu A, Rescigno M, Myles J, Stratakis CA. Family environment and development in children adopted from institutionalized care. Pediatr Res 2022; 91:1562-1570. [PMID: 34040161 PMCID: PMC8617065 DOI: 10.1038/s41390-020-01325-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 11/13/2020] [Accepted: 12/02/2020] [Indexed: 02/03/2023]
Abstract
BACKGROUND After adoption, children exposed to institutionalized care show significant improvement, but incomplete recovery of growth and developmental milestones. There is a paucity of data regarding risk and protective factors in children adopted from institutionalized care. This prospective study followed children recently adopted from institutionalized care to investigate the relationship between family environment, executive function, and behavioral outcomes. METHODS Anthropometric measurements, physical examination, endocrine and bone age evaluations, neurocognitive testing, and behavioral questionnaires were evaluated over a 2-year period with children adopted from institutionalized care and non-adopted controls. RESULTS Adopted children had significant deficits in growth, cognitive, and developmental measurements compared to controls that improved; however, residual deficits remained. Family cohesiveness and expressiveness were protective influences, associated with less behavioral problems, while family conflict and greater emphasis on rules were associated with greater risk for executive dysfunction. CONCLUSIONS Our data suggest that a cohesive and expressive family environment moderated the effect of pre-adoption adversity on cognitive and behavioral development in toddlers, while family conflict and greater emphasis on rules were associated with greater risk for executive dysfunction. Early assessment of child temperament and parenting context may serve to optimize the fit between parenting style, family environment, and the child's development. IMPACT Children who experience institutionalized care are at increased risk for significant deficits in developmental, cognitive, and social functioning associated with a disruption in the development of the prefrontal cortex. Aspects of the family caregiving environment moderate the effect of early life social deprivation in children. Family cohesiveness and expressiveness were protective influences, while family conflict and greater emphasis on rules were associated with a greater risk for executive dysfunction problems. This study should be viewed as preliminary data to be referenced by larger studies investigating developmental and behavioral outcomes of children adopted from institutional care.
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Affiliation(s)
- Margaret F. Keil
- grid.94365.3d0000 0001 2297 5165Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD USA
| | - Adela Leahu
- grid.94365.3d0000 0001 2297 5165Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD USA
| | - Megan Rescigno
- grid.266818.30000 0004 1936 914XUniversity of Nevada School of Medicine, Reno, NV USA
| | - Jennifer Myles
- grid.94365.3d0000 0001 2297 5165Nutrition Department, Clinical Center, National Institutes of Health, Bethesda, MD USA
| | - Constantine A. Stratakis
- grid.94365.3d0000 0001 2297 5165Section on Endocrinology and Genetics, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD USA
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24
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Sydnor VJ, Larsen B, Bassett DS, Alexander-Bloch A, Fair DA, Liston C, Mackey AP, Milham MP, Pines A, Roalf DR, Seidlitz J, Xu T, Raznahan A, Satterthwaite TD. Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology. Neuron 2021; 109:2820-2846. [PMID: 34270921 PMCID: PMC8448958 DOI: 10.1016/j.neuron.2021.06.016] [Citation(s) in RCA: 226] [Impact Index Per Article: 75.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 05/24/2021] [Accepted: 06/11/2021] [Indexed: 12/11/2022]
Abstract
The human brain undergoes a prolonged period of cortical development that spans multiple decades. During childhood and adolescence, cortical development progresses from lower-order, primary and unimodal cortices with sensory and motor functions to higher-order, transmodal association cortices subserving executive, socioemotional, and mentalizing functions. The spatiotemporal patterning of cortical maturation thus proceeds in a hierarchical manner, conforming to an evolutionarily rooted, sensorimotor-to-association axis of cortical organization. This developmental program has been characterized by data derived from multimodal human neuroimaging and is linked to the hierarchical unfolding of plasticity-related neurobiological events. Critically, this developmental program serves to enhance feature variation between lower-order and higher-order regions, thus endowing the brain's association cortices with unique functional properties. However, accumulating evidence suggests that protracted plasticity within late-maturing association cortices, which represents a defining feature of the human developmental program, also confers risk for diverse developmental psychopathologies.
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Affiliation(s)
- Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Danielle S Bassett
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Electrical & Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Physics & Astronomy, College of Arts & Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Santa Fe Institute, Santa Fe, NM 87501, USA
| | - Aaron Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN 55414, USA
| | - Conor Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10065, USA
| | - Allyson P Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY 10962, USA
| | - Adam Pines
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David R Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jakob Seidlitz
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Armin Raznahan
- Section on Developmental Neurogenomics, NIMH Intramural Research Program, NIH, Bethesda, MD 20892, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA.
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25
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Gharaylou Z, Sahraian MA, Hadjighassem M, Kohanpour M, Doosti R, Nahardani S, Moghadasi AN. Widespread Disruptions of White Matter in Familial Multiple Sclerosis: DTI and NODDI Study. Front Neurol 2021; 12:678245. [PMID: 34484098 PMCID: PMC8415561 DOI: 10.3389/fneur.2021.678245] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 06/14/2021] [Indexed: 11/29/2022] Open
Abstract
Diffusion tensor imaging (DTI) is a noninvasive, quantitative MRI technique that measures white matter (WM) integrity. Many brain dimensions are heritable, including white matter integrity measured with DTI. Family studies are valuable to provide insights into the interactive effects of non-environmental factors on multiple sclerosis (MS). To examine the contribution of familial factors to the diffusion signals across WM microstructure, we performed DTI and calculated neurite orientation dispersion plus density imaging (NODDI) diffusion parameters in two patient groups comprising familial and sporadic forms of multiple sclerosis and their unaffected relatives. We divided 111 subjects (49 men and 62 women: age range 19-60) into three groups conforming to their MS history. The familial MS group included 30 participants (patients; n = 16, healthy relatives; n = 14). The sporadic group included 41 participants (patients; n = 10, healthy relatives; n = 31). Forty age-matched subjects with no history of MS in their families were defined as the control group. To study white matter integrity, two methods were employed: one for calculating the mean of DTI, FA, and MD parameters on 18 tracts using Tracts Constrained by Underlying Anatomy (TRACULA) and the other for whole brain voxel-based analysis using tract-based spatial statistics (TBSS) on NDI and ODI parameters derived from NODDI and DTI parameters. Voxel-based analysis showed considerable changes in FA, MD, NDI, and ODI in the familial group when compared with the control group, reflecting widespread impairment of white matter in this group. The analysis of 18 tracts with TRACULA revealed increased MD and FA reduction in more tracts (left and right ILF, UNC, and SLFT, forceps major and minor) in familial MS patients vs. the control group. There were no significant differences between the patient groups. We found no consequential changes in healthy relatives of both patient groups in voxel-based and tract analyses. Considering the multifactorial etiology of MS, familial studies are of great importance to clarify the effects of certain predisposing factors on demyelinating brain pathology.
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Affiliation(s)
- Zeinab Gharaylou
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Ali Sahraian
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahmoudreza Hadjighassem
- Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohsen Kohanpour
- Neuroimaging and Analysis Group (NIAG), Research Center for Molecular and Cellular Imaging, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Rozita Doosti
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Shima Nahardani
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Abdorreza Naser Moghadasi
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
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26
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Fung MH, Taylor BK, Lew BJ, Frenzel MR, Eastman JA, Wang YP, Calhoun VD, Stephen JM, Wilson TW. Sexually dimorphic development in the cortical oscillatory dynamics serving early visual processing. Dev Cogn Neurosci 2021; 50:100968. [PMID: 34102602 PMCID: PMC8187257 DOI: 10.1016/j.dcn.2021.100968] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Revised: 04/02/2021] [Accepted: 05/25/2021] [Indexed: 11/25/2022] Open
Abstract
Visual processing dynamics continue to develop throughout childhood and adolescence. Visual alpha response power differed between males and females. Sex and age interacted to modulate visual gamma responses. Peak frequency predicted response power above and beyond the effects of age and sex.
Successful interaction with one’s visual environment is paramount to developing and performing many basic and complex mental functions. Although major aspects of visual development are completed at an early age, other structural and functional components of visual processing appear to be dynamically changing across a much more protracted period extending into late childhood and adolescence. However, the underlying neurophysiological changes and cortical oscillatory dynamics that support maturation of the visual system during this developmental period remain poorly understood. The present study utilized magnetoencephalography (MEG) to investigate maturational changes in the neural dynamics serving basic visual processing during childhood and adolescence (ages 9–15, n = 69). Our key results included robust sex differences in alpha oscillatory activity within the left posterior parietal cortex, and sex-by-age interactions in gamma activity in the right lingual gyrus and superior parietal lobule. Hierarchical regression revealed that the peak frequency of both the alpha and gamma responses predicted response power in parietal regions above and beyond the noted effects of age and sex. These findings affirm the view that neural oscillations supporting visual processing develop over a much more protracted period, and illustrate that these maturational trajectories are influenced by numerous elements, including age, sex, and individual variation.
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Affiliation(s)
- Madison H Fung
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA
| | - Brittany K Taylor
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA
| | - Brandon J Lew
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA; College of Medicine, University of Nebraska Medical Center, Omaha, NE, USA
| | - Michaela R Frenzel
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA
| | - Jacob A Eastman
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA
| | - Yu-Ping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, LA, USA
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) [Georgia State University, Georgia Institute of Technology, Emory University], Atlanta, GA, USA
| | | | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA.
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27
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Richmond S, Beare R, Johnson KA, Allen NB, Seal ML, Whittle S. Towards understanding neurocognitive mechanisms of parenting: Maternal behaviors and structural brain network organization in late childhood. Hum Brain Mapp 2021; 42:1845-1862. [PMID: 33528857 PMCID: PMC7978130 DOI: 10.1002/hbm.25334] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 12/14/2020] [Accepted: 12/18/2020] [Indexed: 02/07/2023] Open
Abstract
A substantial body of knowledge suggests that exposure to adverse family environments - including violence and neglect - influences many aspects of brain development. Relatively less attention has been directed toward the influence of "normative" differences in parenting behaviors. Given the rapid brain reorganization during late childhood, parenting behaviors are particularly likely to impact the structure of the brain during this time. This study investigated associations between maternal parenting behaviors and the organization of structural brain networks in late childhood, as measured by structural covariance. One hundred and forty-five typically developing 8-year-olds and their mothers completed questionnaire measures and two observed interaction tasks; magnetic resonance imaging (MRI) scans were obtained from the children. Measures of maternal negative, positive, and communicative behavior were derived from the interaction tasks. Structural covariance networks based on partial correlations between cortical thickness estimates were constructed and estimates of modularity were obtained using graph theoretical analysis. High levels of negative maternal behavior were associated with low modularity. Minimal support was found for an association between positive maternal behaviors and modularity and between maternal communicative behaviors and modularity. Our findings suggest that variation in negative maternal behavior is associated with the structural organization of brain networks in children.
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Affiliation(s)
- Sally Richmond
- Melbourne Neuropsychiatry Centre, Department of PsychiatryThe University of Melbourne and Melbourne HealthMelbourneVictoriaAustralia
- Melbourne School of Psychological SciencesThe University of MelbourneParkvilleVictoriaAustralia
- Turner Institute for Brain and Mental HealthMonash UniversityMelbourneVictoriaAustralia
| | - Richard Beare
- Department of Developmental ImagingMurdoch Children's Research InstituteParkvilleVictoriaAustralia
- Department of MedicineMonash UniversityMelbourneVictoriaAustralia
| | - Katherine A. Johnson
- Melbourne School of Psychological SciencesThe University of MelbourneParkvilleVictoriaAustralia
| | - Nicholas B. Allen
- Melbourne School of Psychological SciencesThe University of MelbourneParkvilleVictoriaAustralia
- Department of PsychologyUniversity of OregonEugeneOregonUSA
| | - Marc L. Seal
- Department of Developmental ImagingMurdoch Children's Research InstituteParkvilleVictoriaAustralia
- Department for PaediatricsThe University of MelbourneParkvilleVictoriaAustralia
| | - Sarah Whittle
- Melbourne Neuropsychiatry Centre, Department of PsychiatryThe University of Melbourne and Melbourne HealthMelbourneVictoriaAustralia
- Melbourne School of Psychological SciencesThe University of MelbourneParkvilleVictoriaAustralia
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Sultan AA, Kennedy KG, Fiksenbaum L, MacIntosh BJ, Goldstein BI. Neurostructural Correlates of Cannabis Use in Adolescent Bipolar Disorder. Int J Neuropsychopharmacol 2021; 24:181-190. [PMID: 33103721 PMCID: PMC7968618 DOI: 10.1093/ijnp/pyaa077] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 10/20/2020] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Little is known regarding the association of cannabis use with brain structure in adolescents with bipolar disorder (BD). This subject is timely, given expanded availability of cannabis contemporaneously with increased social acceptance and diminished societal constraints to access. Therefore, we set out to examine this topic in a sample of adolescents with BD and healthy control (HC) adolescents. METHODS Participants included 144 adolescents (47 BD with cannabis use [BDCB+; including 13 with cannabis use disorder], 34 BD without cannabis use [BDCB-], 63 HC without cannabis use) ages 13-20 years. FreeSurfer-processed 3T MRI with T1-weighted contrast yielded measures of cortical thickness, surface area (SA), and volume. Region of interest (amygdala, hippocampus, ventrolateral prefrontal cortex, ventromedial prefrontal cortex, and anterior cingulate cortex) analyses and exploratory vertex-wise analysis were undertaken. A general linear model tested for between-group differences, accounting for age, sex, and intracranial volume. RESULTS Vertex-wise analysis revealed significant group effects in frontal and parietal regions. In post-hoc analyses, BDCB+ exhibited larger volume and SA in parietal regions, and smaller thickness in frontal regions, relative to HC and BDCB-. BDCB- had smaller volume, SA, and thickness in parietal and frontal regions relative to HC. There were no significant region of interest findings after correcting for multiple comparisons. CONCLUSION This study found that cannabis use is associated with differences in regional brain structure among adolescents with BD. Future prospective studies are necessary to determine the direction of the observed association and to assess for dose effects.
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Affiliation(s)
- Alysha A Sultan
- Centre for Youth Bipolar Disorder, Sunnybrook Health Sciences Centre, Toronto, Canada
- Department of Pharmacology, University of Toronto, Toronto, Canada
| | - Kody G Kennedy
- Centre for Youth Bipolar Disorder, Sunnybrook Health Sciences Centre, Toronto, Canada
- Department of Pharmacology, University of Toronto, Toronto, Canada
| | - Lisa Fiksenbaum
- Centre for Youth Bipolar Disorder, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Bradley J MacIntosh
- Hurvitz Brain Sciences & Physical Sciences, Sunnybrook Research Institute, Toronto, Canada
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Benjamin I Goldstein
- Centre for Youth Bipolar Disorder, Sunnybrook Health Sciences Centre, Toronto, Canada
- Department of Pharmacology, University of Toronto, Toronto, Canada
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, Toronto, Canada
- Department of Psychiatry, University of Toronto, Toronto, Canada
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An alternative approach to future diagnostic standards for major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2021; 105:110133. [PMID: 33049324 DOI: 10.1016/j.pnpbp.2020.110133] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 10/06/2020] [Indexed: 12/17/2022]
Abstract
During the period extending from 1780 to 1880, the conceptualization of melancholia changed from an intellectual to a mood model. The modern view of depression, based on Kraepelinian dualism, has reflected changes in opinion on psychiatric taxonomy of individual melancholia. From the point of view of an "operational revolution," the diagnostic criteria for major depressive disorder in the Diagnostic and Statistical Manual of Mental Disorders, 3rd edition (DSM-III) were based on a neoKraepelinian approach rooted in disease essentialism. In the revision process from the DSM-IV to the DSM-5, a combined dimensional and categorial approach was used. In the DSM-5, the diagnostic criteria for major depressive disorder are polythetic and operational in approach reflecting the heterogeneity of major depressive disorder. Although 227 different symptom combinations fulfilling the diagnostic criteria for major depressive disorder can be theoretically calculated, certain symptom combinations are more prevalent than others in real clinical situations. The heterogeneity of these operational criteria for major depressive disorder have been criticized in a manner informed by the Wittgensteinian analogy of the language game. Herein, our network analysis proposes a novel perspective on the psychopathology of major depressive disorder. The novel approach suggested here may lay the foundation for a redefinition of the traditional taxonomy of depression.
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Human Connectome Project: heritability of brain volumes in young healthy adults. Exp Brain Res 2021; 239:1273-1286. [PMID: 33611617 DOI: 10.1007/s00221-021-06057-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Accepted: 02/04/2021] [Indexed: 01/17/2023]
Abstract
Here we report on the heritability and Intraclass Correlation Coefficients (ICCs) of brain volumes in 1,103 young healthy adults with mean age 29.2 years. Among them are: 153 monozygotic (MZ) twin pairs and 86 dizygotic (DZ) twin pairs, 133 non-twin siblings of MZ twins, 76 non-twin siblings of DZ twins, 335 siblings, and 81 unrelated individuals. ICCs were calculated between pairs of the following genetic groups: (1) MZ twins; (2) DZ twins; (3) MZ twins-their singleton siblings; (4) DZ twins-their singleton siblings; (5) siblings (SB); and (6) unrelated individuals (NR). We studied 4 brain groups: global, lobar, subcortical, and cortical brain regions. For each of 4 brain groups we found the same order of ICCs ranging from the highest values for MZ twins, statistically significantly smaller for the DZ twins and 3 sibling groups, and practically zero for NR. The DZ twins and 3 sibling groups were not different. No hemispheric difference was found in any genetic group. Among brain groups, the highest heritability was for the global regions, followed by lobar and subcortical groups. Only the cortical brain group heritability was statistically lower than other brain groups. We found less genetic control on the left hemisphere than on the right but no significant difference between hemispheres, and no hemispheric lateralization of heritability for any of the brain groups. These findings document substantial and systematic heritability of global and regional brain volumes.
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Barber AD, Hegarty CE, Lindquist M, Karlsgodt KH. Heritability of Functional Connectivity in Resting State: Assessment of the Dynamic Mean, Dynamic Variance, and Static Connectivity across Networks. Cereb Cortex 2021; 31:2834-2844. [PMID: 33429433 DOI: 10.1093/cercor/bhaa391] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 11/25/2020] [Accepted: 12/02/2020] [Indexed: 01/26/2023] Open
Abstract
Recent efforts to evaluate the heritability of the brain's functional connectome have predominantly focused on static connectivity. However, evaluating connectivity changes across time can provide valuable insight about the inherent dynamic nature of brain function. Here, the heritability of Human Connectome Project resting-state fMRI data was examined to determine whether there is a genetic basis for dynamic fluctuations in functional connectivity. The dynamic connectivity variance, in addition to the dynamic mean and standard static connectivity, was evaluated. Heritability was estimated using Accelerated Permutation Inference for the ACE (APACE), which models the additive genetic (h2), common environmental (c2), and unique environmental (e2) variance. Heritability was moderate (mean h2: dynamic mean = 0.35, dynamic variance = 0.45, and static = 0.37) and tended to be greater for dynamic variance compared to either dynamic mean or static connectivity. Further, heritability of dynamic variance was reliable across both sessions for several network connections, particularly between higher-order cognitive and visual networks. For both dynamic mean and static connectivity, similar patterns of heritability were found across networks. The findings support the notion that dynamic connectivity is genetically influenced. The flexibility of network connections, not just their strength, is a heritable endophenotype that may predispose trait behavior.
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Affiliation(s)
- Anita D Barber
- Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, New York, 11004, USA.,Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, New York, 11030, USA.,Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11549, USA
| | | | - Martin Lindquist
- Department of Biostatistics, Johns Hopkins University, Baltimore, 21205, USA
| | - Katherine H Karlsgodt
- Department of Psychology, University of California, Los Angeles, 90095, USA.,Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, 90095, USA
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Park SC, Kim YK. Challenges and Strategies for Current Classifications of Depressive Disorders: Proposal for Future Diagnostic Standards. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1305:103-116. [PMID: 33834397 DOI: 10.1007/978-981-33-6044-0_7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/24/2023]
Abstract
The Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition (DSM-IV) was revised based on a combination of a categorical and a dimensional approach such that in the DSM, Fifth Edition (DSM-5), depressive disorders have been separated as a distinctive disease entity from bipolar disorders, consistent with the deconstruction of Kraepelinian dualism. Additionally, the diagnostic thresholds of depressive disorders may be reduced due to the addition of "hopelessness" to the subjective descriptors of depressed mood and the removal of the "bereavement exclusion." Manic/hypomanic, psychotic, and anxious symptoms in major depressive disorder (MDD) and other depressive disorders are described using the transdiagnostic specifiers of "with mixed features," "with psychotic features," and "with anxious distress," respectively. Additionally, due to the polythetic and operational characteristics of the DSM-5 diagnostic criteria, the heterogeneity of MDD is inevitable. Thus, 227 different symptom combinations fulfill the DSM-5 diagnostic criteria for MDD. This heterogeneity of MDD is criticized in view of the Wittgensteinian analogy of language game. Depression subtypes determined by disturbances in monoamine levels and the severity of the disease have been identified in the literature. According to a review of the Gottesman and Gould criteria, neuroticism, morning cortisol, cortisol awakening response, asymmetry in frontal cortical activity on electroencephalography (EEG), and probabilistic reward learning, among other variables, are evidenced as endophenotypes for depressive disorders. Network analysis has been proposed as a potential method to compliment the limitations of current diagnostic criteria and to explore the pathways between depressive symptoms, as well as to identify novel and interesting relationships between depressive symptoms. Based on the literature on network analysis in this field, no differences in the centrality index of the DSM and non-DSM symptoms were repeatedly present among patients with MDD. Furthermore, MDD and other depressive syndromes include two of the Research Domain Criteria (RDoC), including the Loss construct within the Negative Valence Systems domains and various Reward constructs within the Positive Valence Systems domain.
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Affiliation(s)
- Seon-Cheol Park
- Department of Psychiatry, Hanyang University Guri Hospital, Guri, Republic of Korea
| | - Yong-Ku Kim
- Department of Psychiatry, Korea University Ansan Hospital, College of Medicine, Ansan, Republic of Korea.
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Parental Education, Household Income, and Cortical Surface Area among 9-10 Years Old Children: Minorities' Diminished Returns. Brain Sci 2020; 10:brainsci10120956. [PMID: 33317053 PMCID: PMC7763341 DOI: 10.3390/brainsci10120956] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 12/04/2020] [Accepted: 12/07/2020] [Indexed: 12/16/2022] Open
Abstract
Introduction: Although the effects of parental education and household income on children's brain development are well established, less is known about possible variation in these effects across diverse racial and ethnic groups. According to the Minorities' Diminished Returns (MDRs) phenomenon, due to structural racism, social stratification, and residential segregation, parental educational attainment and household income show weaker effects for non-White than White children. Purpose: Built on the MDRs framework and conceptualizing race as a social rather than a biological factor, this study explored racial and ethnic variation in the magnitude of the effects of parental education and household income on children's whole-brain cortical surface area. Methods: For this cross-sectional study, we used baseline socioeconomic and structural magnetic resonance imaging (sMRI) data of the Adolescent Brain Cognitive Development (ABCD) study. Our analytical sample was 10,262 American children between ages 9 and 10. The independent variables were parental education and household income. The primary outcome was the children's whole-brain cortical surface area. Age, sex, and family marital status were covariates. Race and ethnicity were the moderators. We used mixed-effects regression models for data analysis as participants were nested within families and study sites. Results: High parental education and household income were associated with larger children's whole-brain cortical surface area. The effects of high parental education and high household income on children's whole-brain cortical surface area were modified by race. Compared to White children, Black children showed a diminished return of high parental education on the whole-brain cortical surface area when compared to White children. Asian American children showed weaker effects of household income on the whole-brain cortical surface area when compared to White children. We could not find differential associations between parental education and household income with the whole-brain cortical surface area, when compared to White children, for non-Hispanic and Hispanic children. Conclusions: The effects of parental educational attainment and household income on children's whole-brain cortical surface area are weaker in non-White than White families. Although parental education and income contribute to children's brain development, these effects are unequal across racial groups.
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Kruggel F, Solodkin A. Heritability of Structural Patterning in the Human Cerebral Cortex. Neuroimage 2020; 221:117169. [PMID: 32693166 DOI: 10.1016/j.neuroimage.2020.117169] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 06/29/2020] [Accepted: 07/11/2020] [Indexed: 01/11/2023] Open
Abstract
Genetic influences that govern the spatial patterning of the human cortex and its structural variability are still incompletely known. We analyzed structural MR images in twins, siblings, and pairs of unrelated subjects. A comprehensive set of methods was employed to quantify properties of cortical features at different spatial scales. Measures were used to assess the influence of genetic similarity on structural patterning. Results indicated that: (1) Genetic effects significantly influence all structural features assessed here at all spatial resolutions, albeit at different strengths. (2) While strong genetic effects were found at the whole-brain and hemisphere level, effects were weaker at the regional and vertex level, depending on the measure under study. (3) Besides cortical thickness, sulcal (geodesic) depth was found to be under strong genetic control. The local pattern indicated that two axes along (a) the anterior-posterior direction (insula to parieto-occipital sulcus), and (b) superior-inferior direction (central sulcus to callosal sulcus) presumably determine the segregation of four quadrants in each hemisphere early in development. (4) While strong structural asymmetries were found at the regional level, genetic influences on laterality were relatively minor.
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Affiliation(s)
- Frithjof Kruggel
- Department of Biomedical Engineering, University of California, Irvine, USA.
| | - Ana Solodkin
- School of Behavioral and Brain Sciences, University of Texas, Dallas, USA
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Schmitt JE, Raznahan A, Clasen LS, Wallace GL, Pritikin JN, Lee NR, Giedd JN, Neale MC. The Dynamic Associations Between Cortical Thickness and General Intelligence are Genetically Mediated. Cereb Cortex 2020; 29:4743-4752. [PMID: 30715232 DOI: 10.1093/cercor/bhz007] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Revised: 12/04/2018] [Indexed: 11/14/2022] Open
Abstract
The neural substrates of intelligence represent a fundamental but largely uncharted topic in human developmental neuroscience. Prior neuroimaging studies have identified modest but highly dynamic associations between intelligence and cortical thickness (CT) in childhood and adolescence. In a separate thread of research, quantitative genetic studies have repeatedly demonstrated that most measures of intelligence are highly heritable, as are many brain regions associated with intelligence. In the current study, we integrate these 2 streams of prior work by examining the genetic contributions to CT-intelligence relationships using a genetically informative longitudinal sample of 813 typically developing youth, imaged with high-resolution MRI and assessed with Wechsler Intelligence Scales (IQ). In addition to replicating the phenotypic association between multimodal association cortex and language centers with IQ, we find that CT-IQ covariance is nearly entirely genetically mediated. Moreover, shared genetic factors drive the rapidly evolving landscape of CT-IQ relationships in the developing brain.
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Affiliation(s)
- J Eric Schmitt
- Departments of Radiology and Psychiatry, Division of Neuroradiology, Brain Behavior Laboratory, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, USA
| | - Armin Raznahan
- Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Building 10, Room 4D18, 10 Center Drive, Bethesda, MD, USA
| | - Liv S Clasen
- Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Building 10, Room 4D18, 10 Center Drive, Bethesda, MD, USA
| | - Greg L Wallace
- Department of Speech, Language, and Hearing Sciences, The George Washington University, 2115 G Street NW, Hall of Government, Room 226, Washington, DC, USA
| | - Joshua N Pritikin
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980126, Richmond, VA, USA
| | - Nancy Raitano Lee
- Department of Psychology, Drexel University, 3201 Chestnut Street, Stratton Hall, Room 123E, Philadelphia, PA, USA
| | - Jay N Giedd
- Department of Psychiatry, University of California at San Diego, 9500 Gilman Drive #0949, La Jolla, CA, USA
| | - Michael C Neale
- Departments of Psychiatry and Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980126, Richmond, VA, USA
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Schmitt JE, Raznahan A, Liu S, Neale MC. The Heritability of Cortical Folding: Evidence from the Human Connectome Project. Cereb Cortex 2020; 31:702-715. [PMID: 32959043 DOI: 10.1093/cercor/bhaa254] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 08/09/2020] [Accepted: 08/10/2020] [Indexed: 12/13/2022] Open
Abstract
The mechanisms underlying cortical folding are incompletely understood. Prior studies have suggested that individual differences in sulcal depth are genetically mediated, with deeper and ontologically older sulci more heritable than others. In this study, we examine FreeSurfer-derived estimates of average convexity and mean curvature as proxy measures of cortical folding patterns using a large (N = 1096) genetically informative young adult subsample of the Human Connectome Project. Both measures were significantly heritable near major sulci and primary fissures, where approximately half of individual differences could be attributed to genetic factors. Genetic influences near higher order gyri and sulci were substantially lower and largely nonsignificant. Spatial permutation analysis found that heritability patterns were significantly anticorrelated to maps of evolutionary and neurodevelopmental expansion. We also found strong phenotypic correlations between average convexity, curvature, and several common surface metrics (cortical thickness, surface area, and cortical myelination). However, quantitative genetic models suggest that correlations between these metrics are largely driven by nongenetic factors. These findings not only further our understanding of the neurobiology of gyrification, but have pragmatic implications for the interpretation of heritability maps based on automated surface-based measurements.
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Affiliation(s)
- J Eric Schmitt
- Departments of Radiology and Psychiatry, Division of Neuroradiology, Brain Behavior Laboratory, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Armin Raznahan
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Siyuan Liu
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Michael C Neale
- Departments of Psychiatry and Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA 23298-980126, USA
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Pizzagalli F, Auzias G, Yang Q, Mathias SR, Faskowitz J, Boyd JD, Amini A, Rivière D, McMahon KL, de Zubicaray GI, Martin NG, Mangin JF, Glahn DC, Blangero J, Wright MJ, Thompson PM, Kochunov P, Jahanshad N. The reliability and heritability of cortical folds and their genetic correlations across hemispheres. Commun Biol 2020; 3:510. [PMID: 32934300 PMCID: PMC7493906 DOI: 10.1038/s42003-020-01163-1] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 07/24/2020] [Indexed: 12/22/2022] Open
Abstract
Cortical folds help drive the parcellation of the human cortex into functionally specific regions. Variations in the length, depth, width, and surface area of these sulcal landmarks have been associated with disease, and may be genetically mediated. Before estimating the heritability of sulcal variation, the extent to which these metrics can be reliably extracted from in-vivo MRI must be established. Using four independent test-retest datasets, we found high reliability across the brain (intraclass correlation interquartile range: 0.65-0.85). Heritability estimates were derived for three family-based cohorts using variance components analysis and pooled (total N > 3000); the overall sulcal heritability pattern was correlated to that derived for a large population cohort (N > 9000) calculated using genomic complex trait analysis. Overall, sulcal width was the most heritable metric, and earlier forming sulci showed higher heritability. The inter-hemispheric genetic correlations were high, yet select sulci showed incomplete pleiotropy, suggesting hemisphere-specific genetic influences.
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Grants
- P41 EB015922 NIBIB NIH HHS
- R01 EB015611 NIBIB NIH HHS
- P01 AG026276 NIA NIH HHS
- R21 NS064534 NINDS NIH HHS
- R01 MH078111 NIMH NIH HHS
- R01 HD050735 NICHD NIH HHS
- R01 NS056307 NINDS NIH HHS
- R01 MH121246 NIMH NIH HHS
- P50 MH071616 NIMH NIH HHS
- R03 EB012461 NIBIB NIH HHS
- R01 AG059874 NIA NIH HHS
- U24 RR021382 NCRR NIH HHS
- P30 AG066444 NIA NIH HHS
- P01 AG003991 NIA NIH HHS
- P50 AG005681 NIA NIH HHS
- U54 EB020403 NIBIB NIH HHS
- R01 MH117601 NIMH NIH HHS
- U54 MH091657 NIMH NIH HHS
- R01 AG021910 NIA NIH HHS
- R01 MH078143 NIMH NIH HHS
- P41 RR015241 NCRR NIH HHS
- S10 OD023696 NIH HHS
- R01 MH083824 NIMH NIH HHS
- This research was funded in part by NIH ENIGMA Center grant U54 EB020403, supported by the Big Data to Knowledge (BD2K) Centers of Excellence program funded by a cross-NIH initiative. Additional grant support was provided by: R01 AG059874, R01 MH117601, R01 MH121246, and P41 EB015922. QTIM was supported by NIH R01 HD050735, and the NHMRC 486682, Australia; GOBS: Financial support for this study was provided by the National Institute of Mental Health grants MH078143 (PI: DC Glahn), MH078111 (PI: J Blangero), and MH083824 (PI: DC Glahn & J Blangero); HCP data were provided [in part] by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University; UK Biobank: This research was conducted using the UK Biobank Resource under Application Number ‘11559’; BrainVISA’s Morphologist software development received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Grant Agreement No 720270 & 785907 (Human Brain ProjectSGA1 & SGA2), and by the FRM DIC20161236445. OASIS: Cross-Sectional: Principal Investigators: D. Marcus, R. Buckner, J. Csernansky J. Morris; P50 AG05681, P01 AG03991, P01 AG026276, R01 AG021910, P20 MH071616, U24 RR021382. KKI was supported by NIH grants NCRR P41 RR015241 (Peter C.M. van Zijl), 1R01NS056307 (Jerry Prince), 1R21NS064534-01A109 (Bennett A. Landman/Jerry L. Prince), 1R03EB012461-01 (Bennett A. Landman). Neda Jahanshad and Paul Thompson are MPIs of a research project grant from Biogen, Inc. (PO 969323).
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Affiliation(s)
- Fabrizio Pizzagalli
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA.
| | - Guillaume Auzias
- Institut de Neurosciences de la Timone, UMR7289, Aix-Marseille Université & CNRS, Marseille, France
| | - Qifan Yang
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Samuel R Mathias
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - Joshua Faskowitz
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Joshua D Boyd
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Armand Amini
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Denis Rivière
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette, France
- CATI, Multicenter Neuroimaging Platform, Paris, France
| | - Katie L McMahon
- School of Clinical Sciences and Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Greig I de Zubicaray
- Faculty of Health, Queensland University of Technology (QUT), Brisbane, QLD, 4000, Australia
| | | | - Jean-François Mangin
- Université Paris-Saclay, CEA, CNRS, Neurospin, Baobab, Gif-sur-Yvette, France
- CATI, Multicenter Neuroimaging Platform, Paris, France
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Yale University School of Medicine, New Haven, CT, USA
| | - John Blangero
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, 4072, Australia
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA.
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Parsley I, Zhang Z, Hausmann M, Lerdahl A, Vaughan B, Edwards R, Hwang S. Effectiveness of Stimulant Medications on Disruptive Behavior and Mood Problems in Young Children. CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE 2020; 18:402-411. [PMID: 32702219 PMCID: PMC7383001 DOI: 10.9758/cpn.2020.18.3.402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Revised: 04/14/2020] [Accepted: 05/06/2020] [Indexed: 11/20/2022]
Abstract
Objective There are very few studies on the effectiveness of stimulant medications for the treatment of disruptive mood and behavior problems in young children (less than 7 years) with Disruptive Behavior Disorders (DBD). The current study aims to determine whether young children (ages 4−7) in a long-term, intensive outpatient behavioral treatment program who are receiving stimulant medications show greater improvement in mood and behavior problems compared to peers who did not. Methods A retrospective chart review was conducted for 97 participants diagnosed with DBD, aged 4−7 years old who were enrolled in an intensive outpatient behavioral intervention program. Pre- and post-intervention Child Behavior Checklist (CBCL) scores for disruptive behavior and mood problems were compared between the children who received stimulant medications and those who did not. Results Paired t tests showed a statistically significant improvement in CBCL outcomes between pre- and post-intervention scores of disruptive behavior and mood problems. ANCOVA analysis, however, showed no clear further improvement in those same CBCL scores in the participants who received stimulant medications compared to the participants who did not. CBCL scores for Conduct Disorder were marginally significant for less improvement for the participants who received stimulant medications. Conclusion This retrospective review suggests a possibility that stimulant medications may not provide additional benefit for the long-term treatment of disruptive behavior and mood problems in young children under age 7. Future study is warranted to evaluate the efficacy/effectiveness of stimulant medications in the treatment of disruptive behavior and mood problems in this population.
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Affiliation(s)
- Ian Parsley
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Zhuo Zhang
- China University of Political Science and Law, School of Psychology, Beijing, China
| | - Mark Hausmann
- Daybreak Mental and Behavioral Health, Papillion, NE, USA
| | - Arica Lerdahl
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, USA
| | - Brigette Vaughan
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, USA
| | - Ryan Edwards
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, USA
| | - Soonjo Hwang
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, NE, USA
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van der Meulen M, Wierenga LM, Achterberg M, Drenth N, van IJzendoorn MH, Crone EA. Genetic and environmental influences on structure of the social brain in childhood. Dev Cogn Neurosci 2020; 44:100782. [PMID: 32716847 PMCID: PMC7374548 DOI: 10.1016/j.dcn.2020.100782] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Revised: 03/30/2020] [Accepted: 04/08/2020] [Indexed: 11/17/2022] Open
Abstract
Prosocial behavior and empathy are important aspects of developing social relations in childhood. Prior studies showed protracted structural development of social brain regions associated with prosocial behavior. However, it remains unknown how structure of the social brain is influenced by genetic or environmental factors, and whether overlapping heritability factors explain covariance in structure of the social brain and behavior. The current study examined this hypothesis in a twin sample (aged 7–9-year; N = 512). Bilateral measures of surface area and cortical thickness of the medial prefrontal cortex (mPFC), temporo-parietal junction (TPJ), posterior superior temporal sulcus (pSTS), and precuneus were analyzed. Results showed genetic contributions to surface area and cortical thickness for all brain regions. We found additional shared environmental influences for TPJ, suggesting that this region might be relatively more sensitive to social experiences. Genetic factors also influenced parent-reported prosocial behavior (A = 45%) and empathy (A = 59%). We provided initial evidence that the precuneus shares genetically determined variance with empathy, suggesting a possible small genetic overlap (9%) in brain structure and empathy. These findings show that structure of the social brain and empathy are driven by a combination of genetic and environmental factors, with some factors overlapping for brain structure and behavior.
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Affiliation(s)
- Mara van der Meulen
- Leiden Consortium on Individual Development, Leiden University, the Netherlands; Institute of Psychology, Leiden University, the Netherlands; Leiden Institute for Brain and Cognition, Leiden University, the Netherlands.
| | - Lara M Wierenga
- Leiden Consortium on Individual Development, Leiden University, the Netherlands; Institute of Psychology, Leiden University, the Netherlands; Leiden Institute for Brain and Cognition, Leiden University, the Netherlands
| | - Michelle Achterberg
- Leiden Consortium on Individual Development, Leiden University, the Netherlands; Institute of Psychology, Leiden University, the Netherlands; Leiden Institute for Brain and Cognition, Leiden University, the Netherlands
| | - Nadieh Drenth
- Leiden Consortium on Individual Development, Leiden University, the Netherlands; Department of Radiology, Leiden University Medical Center, the Netherlands
| | - Marinus H van IJzendoorn
- Leiden Consortium on Individual Development, Leiden University, the Netherlands; Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, the Netherlands; School of Clinical Medicine, University of Cambridge, UK
| | - Eveline A Crone
- Leiden Consortium on Individual Development, Leiden University, the Netherlands; Institute of Psychology, Leiden University, the Netherlands; Leiden Institute for Brain and Cognition, Leiden University, the Netherlands
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40
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Hegarty II JP, Lazzeroni LC, Raman MM, Hallmayer JF, Cleveland SC, Wolke ON, Phillips JM, Reiss AL, Hardan AY. Genetic and environmental influences on corticostriatal circuits in twins with autism. J Psychiatry Neurosci 2020; 45:188-197. [PMID: 31603639 PMCID: PMC7828974 DOI: 10.1503/jpn.190030] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Corticostriatal circuits (CSC) have been implicated in the presentation of some restricted and repetitive behaviours (RRBs) in children with autism-spectrum disorder (ASD), and preliminary evidence suggests that disruptions in these pathways may be associated with differences in genetic and environmental influences on brain development. The objective of this investigation was to examine the impact of genetic and environmental factors on CSC regions in twins with and without ASD and to evaluate their relationship with the severity of RRBs. METHODS We obtained T1-weighted MRIs from same-sex monozygotic and dizygotic twin pairs, aged 6–15 years. Good-quality data were available from 48 ASD pairs (n = 96 twins; 30 pairs concordant for ASD, 15 monozygotic and 15 dizygotic; 18 pairs discordant for ASD, 4 monozygotic and 14 dizygotic) and 34 typically developing control pairs (n = 68 twins; 20 monozygotic and 14 dizygotic pairs). We generated structural measures of the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), caudate, putamen, pallidum and thalamus using FreeSurfer. Twin pair comparisons included intraclass correlation analyses and ACE modelling (a2 = additive genetics; c2 = common or shared environment; e2 = unique or nonshared environment). We also assessed correlations with RRB severity. RESULTS Structural variation in CSC regions was predominantly genetically mediated in typically developing twins (a2 = 0.56 to 0.87), except for ACC white matter volume (a2 = 0.42, 95% confidence interval [CI] 0.08 to 0.77). We also observed similar magnitudes of genetic influence in twins with ASD (a2 = 0.65 to 0.97), but the cortical thickness of the ACC (c2 = 0.44, 95% CI 0.22 to 0.66) and OFC (c2 = 0.60, 95% CI 0.25 to 0.95) was primarily associated with environmental factors in only twins with ASD. Twin pair differences in OFC grey matter volume were also correlated with RRB severity and were predominantly environmentally mediated. LIMITATIONS We obtained MRIs on 2 scanners, and analytical approaches could not identify specific genetic and environmental factors. CONCLUSION Genetic factors primarily contribute to structural variation in subcortical CSC regions, regardless of ASD, but environmental factors may exert a greater influence on the development of grey matter thickness in the OFC and ACC in children with ASD. The increased vulnerability of OFC grey matter to environmental influences may also mediate some heterogeneity in RRB severity in children with ASD.
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Affiliation(s)
- John P. Hegarty II
- From the Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA (Hegarty, Lazzeroni, Raman, Hallmayer, Cleveland, Phillips, Reiss, Hardan); the Department of Biomedical Data Science, Stanford University, Stanford, CA (Lazzeroni); and the Department of Anesthesiology, Stanford University, Stanford, CA (Wolke)
| | - Laura C. Lazzeroni
- From the Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA (Hegarty, Lazzeroni, Raman, Hallmayer, Cleveland, Phillips, Reiss, Hardan); the Department of Biomedical Data Science, Stanford University, Stanford, CA (Lazzeroni); and the Department of Anesthesiology, Stanford University, Stanford, CA (Wolke)
| | - Mira M. Raman
- From the Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA (Hegarty, Lazzeroni, Raman, Hallmayer, Cleveland, Phillips, Reiss, Hardan); the Department of Biomedical Data Science, Stanford University, Stanford, CA (Lazzeroni); and the Department of Anesthesiology, Stanford University, Stanford, CA (Wolke)
| | - Joachim F. Hallmayer
- From the Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA (Hegarty, Lazzeroni, Raman, Hallmayer, Cleveland, Phillips, Reiss, Hardan); the Department of Biomedical Data Science, Stanford University, Stanford, CA (Lazzeroni); and the Department of Anesthesiology, Stanford University, Stanford, CA (Wolke)
| | - Sue C. Cleveland
- From the Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA (Hegarty, Lazzeroni, Raman, Hallmayer, Cleveland, Phillips, Reiss, Hardan); the Department of Biomedical Data Science, Stanford University, Stanford, CA (Lazzeroni); and the Department of Anesthesiology, Stanford University, Stanford, CA (Wolke)
| | - Olga N. Wolke
- From the Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA (Hegarty, Lazzeroni, Raman, Hallmayer, Cleveland, Phillips, Reiss, Hardan); the Department of Biomedical Data Science, Stanford University, Stanford, CA (Lazzeroni); and the Department of Anesthesiology, Stanford University, Stanford, CA (Wolke)
| | - Jennifer M. Phillips
- From the Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA (Hegarty, Lazzeroni, Raman, Hallmayer, Cleveland, Phillips, Reiss, Hardan); the Department of Biomedical Data Science, Stanford University, Stanford, CA (Lazzeroni); and the Department of Anesthesiology, Stanford University, Stanford, CA (Wolke)
| | - Allan L. Reiss
- From the Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA (Hegarty, Lazzeroni, Raman, Hallmayer, Cleveland, Phillips, Reiss, Hardan); the Department of Biomedical Data Science, Stanford University, Stanford, CA (Lazzeroni); and the Department of Anesthesiology, Stanford University, Stanford, CA (Wolke)
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Guyer AE. Adolescent Psychopathology: The Role of Brain-based Diatheses, Sensitivities, and Susceptibilities. CHILD DEVELOPMENT PERSPECTIVES 2020; 14:104-109. [PMID: 32655684 DOI: 10.1111/cdep.12365] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
The rates of onset for several forms of psychopathology peak during adolescence, which coincides with the refinement of brain circuitry attuned to expanding social-contextual interactions, stressors, and settings. While some adolescents experience mental health difficulties, most do not develop significant problems. Conceptual work suggests that brain-based individual differences in adolescents' neurobiological susceptibility to their social contexts play a role in the development of psychopathology and well-being. In this article, I summarize evidence supporting the idea that individual differences in brain structure and function moderate the relation between adolescents' social-contextual experiences and psychopathology. I discuss why this approach is important in developmental research designed to identify adolescents at greatest risk for psychopathology or poised for positive outcomes, as well as those who may benefit most from intervention.
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Hegarty JP, Lazzeroni LC, Raman MM, Pegoraro LFL, Monterrey JC, Cleveland SC, Hallmayer JF, Wolke ON, Phillips JM, Reiss AL, Hardan AY. Genetic and Environmental Influences on Lobar Brain Structures in Twins With Autism. Cereb Cortex 2020; 30:1946-1956. [PMID: 31711118 DOI: 10.1093/cercor/bhz215] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 07/26/2019] [Accepted: 08/18/2019] [Indexed: 11/13/2022] Open
Abstract
This investigation examined whether the variation of cerebral structure is associated with genetic or environmental factors in children with autism spectrum disorder (ASD) compared with typically developing (TD) controls. T1-weighted magnetic resonance imaging scans were obtained from twin pairs (aged 6-15 years) in which at least one twin was diagnosed with ASD or both were TD. Good quality data were available from 30 ASD, 18 discordant, and 34 TD pairs (n = 164). Structural measures (volume, cortical thickness, and surface area) were generated with FreeSurfer, and ACE modeling was completed. Lobar structures were primarily genetically mediated in TD twins (a2 = 0.60-0.89), except thickness of the temporal (a2 = 0.33 [0.04, 0.63]) and occipital lobes (c2 = 0.61 [0.45, 0.77]). Lobar structures were also predominantly genetically mediated in twins with ASD (a2 = 0.70-1.00); however, thickness of the frontal (c2 = 0.81 [0.71, 0.92]), temporal (c2 = 0.77 [0.60, 0.93]), and parietal lobes (c2 = 0.87 [0.77, 0.97]), and frontal gray matter (GM) volume (c2 = 0.79 [0.63, 0.95]), were associated with environmental factors. Conversely, occipital thickness (a2 = 0.93 [0.75, 1.11]) did not exhibit the environmental contributions that were found in controls. Differences in GM volume were associated with social communication impairments for the frontal (r = 0.52 [0.18, 0.75]), temporal (r = 0.61 [0.30, 0.80]), and parietal lobes (r = 0.53 [0.19, 0.76]). To our knowledge, this is the first investigation to suggest that environmental factors influence GM to a larger extent in children with ASD, especially in the frontal lobe.
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Affiliation(s)
- John P Hegarty
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Laura C Lazzeroni
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA.,Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Mira M Raman
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Luiz F L Pegoraro
- Department of Psychiatry, University of Campinas, Cidade Universitária Zeferino Vaz, Campinas 13083-970, Brazil
| | - Julio C Monterrey
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Sue C Cleveland
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Joachim F Hallmayer
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Olga N Wolke
- Department of Anesthesiology, Stanford University, Stanford, CA 94305, USA
| | - Jennifer M Phillips
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Allan L Reiss
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
| | - Antonio Y Hardan
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94305, USA
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Mitchell BL, Cuéllar-Partida G, Grasby KL, Campos AI, Strike LT, Hwang LD, Okbay A, Thompson PM, Medland SE, Martin NG, Wright MJ, Rentería ME. Educational attainment polygenic scores are associated with cortical total surface area and regions important for language and memory. Neuroimage 2020; 212:116691. [PMID: 32126298 DOI: 10.1016/j.neuroimage.2020.116691] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 02/06/2020] [Accepted: 02/26/2020] [Indexed: 02/01/2023] Open
Abstract
It is well established that higher cognitive ability is associated with larger brain size. However, individual variation in intelligence exists despite brain size and recent studies have shown that a simple unifactorial view of the neurobiology underpinning cognitive ability is probably unrealistic. Educational attainment (EA) is often used as a proxy for cognitive ability since it is easily measured, resulting in large sample sizes and, consequently, sufficient statistical power to detect small associations. This study investigates the association between three global (total surface area (TSA), intra-cranial volume (ICV) and average cortical thickness) and 34 regional cortical measures with educational attainment using a polygenic scoring (PGS) approach. Analyses were conducted on two independent target samples of young twin adults with neuroimaging data, from Australia (N = 1097) and the USA (N = 723), and found that higher EA-PGS were significantly associated with larger global brain size measures, ICV and TSA (R2 = 0.006 and 0.016 respectively, p < 0.001) but not average thickness. At the regional level, we identified seven cortical regions-in the frontal and temporal lobes-that showed variation in surface area and average cortical thickness over-and-above the global effect. These regions have been robustly implicated in language, memory, visual recognition and cognitive processing. Additionally, we demonstrate that these identified brain regions partly mediate the association between EA-PGS and cognitive test performance. Altogether, these findings advance our understanding of the neurobiology that underpins educational attainment and cognitive ability, providing focus points for future research.
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Affiliation(s)
- Brittany L Mitchell
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia.
| | - Gabriel Cuéllar-Partida
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Katrina L Grasby
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Adrian I Campos
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Lachlan T Strike
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Liang-Dar Hwang
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Aysu Okbay
- Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Sarah E Medland
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Nicholas G Martin
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia; Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD, Australia
| | - Miguel E Rentería
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia; School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
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Schmitt JE, Raznahan A, Liu S, Neale MC. The genetics of cortical myelination in young adults and its relationships to cerebral surface area, cortical thickness, and intelligence: A magnetic resonance imaging study of twins and families. Neuroimage 2020; 206:116319. [PMID: 31678229 PMCID: PMC7871660 DOI: 10.1016/j.neuroimage.2019.116319] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2019] [Revised: 10/14/2019] [Accepted: 10/26/2019] [Indexed: 11/19/2022] Open
Abstract
The cerebral cortex contains a significant quantity of intracortical myelin, but the genetics of cortical myelination (CM) in humans is not well understood. Relatively novel MRI-derived measures now enable the investigation of cortical myelination in large samples. In this study, we use a genetically-informative neuroimaging sample of 1096 young adult subjects from the Human Connectome Project in order to investigate genetic and environmental variation in CM and its relationships with cerebral surface area (SA) and cortical thickness (CT). We found that genetic factors account for approximately 50% of the observed individual differences in mean cortical myelin, 75% of the variation in total SA, and 85% of the variance in global mean CT. Although significant genetic influences were found throughout the cortex, both CM and SA demonstrated a posterior predominance, with disproportionately strong effects in the parietal and occipital lobes and significantly overlapping heritability maps (p < 0.001). Yet despite showing similar spatial heritability patterns, we found evidence that CM is genetically independent from SA at both global and vertex levels; genetically-mediated relationships between CM and CT were similarly small in magnitude. We also found small but statistically significant genetic associations between NIH Toolbox Total Cognition score and CM in the temporal lobe and insula. SA-cognition and CT-cognition correlations were less widespread compared to CM and both patterns were similar to those reported in prior studies.
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Affiliation(s)
- J Eric Schmitt
- Departments of Radiology and Psychiatry, Division of Neuroradiology, Brain Behavior Laboratory, Hospital of the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA, 19104, USA.
| | - Armin Raznahan
- Developmental Neurogenomics Unit, National Institute of Mental Health, Building 10, Room 4C110, 10 Center Drive, Bethesda, MD, 20892, USA.
| | - Siyuan Liu
- Developmental Neurogenomics Unit, National Institute of Mental Health, Building 10, Room 4C110, 10 Center Drive, Bethesda, MD, 20892, USA.
| | - Michael C Neale
- Departments of Psychiatry and Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980126, Richmond, VA, 23298-980126, USA.
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Takahashi S, Keeser D, Rauchmann BS, Schneider-Axmann T, Keller-Varady K, Maurus I, Dechent P, Wobrock T, Hasan A, Schmitt A, Ertl-Wagner B, Malchow B, Falkai P. Effect of aerobic exercise combined with cognitive remediation on cortical thickness and prediction of social adaptation in patients with schizophrenia. Schizophr Res 2020; 216:397-407. [PMID: 31806522 DOI: 10.1016/j.schres.2019.11.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 07/29/2019] [Accepted: 11/03/2019] [Indexed: 01/09/2023]
Abstract
Aerobic exercise is a promising intervention for patients with schizophrenia, but structural neuroplastic effects on brain regions relevant to the pathophysiology of the disease remain unclear. This study aimed to elucidate longitudinal changes in cortical thickness after aerobic exercise intervention in schizophrenia patients and the relationship of these changes to clinical correlates. We investigated 21 schizophrenia patients and 23 healthy controls who performed aerobic exercise and 21 schizophrenia patients who played table soccer. The 12-week exercise intervention was combined with computer-assisted cognitive remediation training from week 6 to week 12. Magnetic resonance imaging (MRI) scans were acquired at baseline and weeks 6, 12, and 24. The thickness of the entorhinal, parahippocampal, and lateral and medial prefrontal cortices was assessed with FreeSurfer 6.0. The schizophrenia aerobic exercise group showed a significant increase of cortical thickness in the right entorhinal cortex at week 6, and we found a significant correlation between the cortical thickness of the right lateral prefrontal cortex at baseline and improvement of social adaptation at week 12. In the schizophrenia table soccer and healthy control groups, we found no significant longitudinal change in cortical thickness through the intervention and follow-up period and no correlation of cortical thickness at baseline with clinical measures. Our results suggest that aerobic exercise in schizophrenia modulates the thickness of the entorhinal cortex, a structure adjacent to the hippocampus. Greater cortical thickness of the right lateral prefrontal cortex appears to predict better clinical response to an aerobic exercise intervention in patients with schizophrenia.
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Affiliation(s)
- Shun Takahashi
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany; Department of Neuropsychiatry, Wakayama Medical University, 811-1 Kimiidera, 6410012, Wakayama, Japan.
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany; Department of Radiology, University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany; Department of Radiology, University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany
| | - Thomas Schneider-Axmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany
| | - Katriona Keller-Varady
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany
| | - Isabel Maurus
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany
| | - Peter Dechent
- Institute for Cognitive Neurology, University Medical Center Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany
| | - Thomas Wobrock
- Department of Psychiatry and Psychotherapy, Georg-August-University, Von-Siebold-Str. 5, 37075, Göttingen, Germany; Centre of Mental Health, County Hospitals Darmstadt-Dieburg, Krankenhausstraße 7, 64823, Groß-Umstadt, Germany
| | - Alkomiet Hasan
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany
| | - Andrea Schmitt
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany; Laboratory of Neuroscience (LIM27), Institute of Psychiatry, University of Sao Paulo, 05403-010, São Paulo, Brazil
| | - Birgit Ertl-Wagner
- Department of Radiology, University Hospital, LMU Munich, Marchioninistraße 15, 81377, Munich, Germany; Department of Medical Imaging, University of Toronto, McCaul Street 263, Toronto, M5T1W7, Ontario, Canada
| | - Berend Malchow
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany; Department of Psychiatry and Psychotherapy, University of Jena, Philosophenweg 3, 07743, Jena, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Nussbaumstraße 7, 80336, Munich, Germany
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Paquette N, Gajawelli N, Lepore N. Structural neuroimaging. HANDBOOK OF CLINICAL NEUROLOGY 2020; 174:251-264. [PMID: 32977882 DOI: 10.1016/b978-0-444-64148-9.00018-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Characterizing the neuroanatomical correlates of brain development is essential in understanding brain-behavior relationships and neurodevelopmental disorders. Advances in brain MRI acquisition protocols and image processing techniques have made it possible to detect and track with great precision anatomical brain development and pediatric neurologic disorders. In this chapter, we provide a brief overview of the modern neuroimaging techniques for pediatric brain development and review key normal brain development studies. Characteristic disorders affecting neurodevelopment in childhood, such as prematurity, attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), epilepsy, and brain cancer, and key neuroanatomical findings are described and then reviewed. Large datasets of typically developing children and children with various neurodevelopmental conditions are now being acquired to help provide the biomarkers of such impairments. While there are still several challenges in imaging brain structures specific to the pediatric populations, such as subject cooperation and tissues contrast variability, considerable imaging research is now being devoted to solving these problems and improving pediatric data analysis.
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Affiliation(s)
- Natacha Paquette
- CIBORG Lab, Department of Radiology, Children's Hospital of Los Angeles and University of Southern California, Los Angeles, CA, United States
| | - Niharika Gajawelli
- CIBORG Lab, Department of Radiology, Children's Hospital of Los Angeles and University of Southern California, Los Angeles, CA, United States
| | - Natasha Lepore
- CIBORG Lab, Department of Radiology, Children's Hospital of Los Angeles and University of Southern California, Los Angeles, CA, United States.
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Schmitt JE, Giedd JN, Raznahan A, Neale MC. The Genetic Contributions to Maturational Coupling in the Human Cerebrum: A Longitudinal Pediatric Twin Imaging Study. Cereb Cortex 2019; 28:3184-3191. [PMID: 28968785 DOI: 10.1093/cercor/bhx190] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2016] [Indexed: 11/13/2022] Open
Abstract
Although prior studies have demonstrated that genetic factors play the dominant role in the patterning of the pediatric brain, it remains unclear how these patterns change over time. Using 1748 longitudinal anatomic MRI scans from 792 healthy twins and siblings, we quantified how genetically mediated inter-regional associations change over time via multivariate longitudinal structural equation modeling. These analyses found that genetic correlations for both lobar volumes and cortical thickness are dynamic, with relatively static effects on surface area. While genetic correlations for lobar volumes decrease over childhood and adolescence, in general they increase for cortical thickness in the second decade of life. Quantification of how genetic factors influence maturational coupling improves our understanding of typical neurodevelopment and informs future molecular genetic analyses.
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Affiliation(s)
- J Eric Schmitt
- Department of Radiology and Psychiatry, Brain Behavior Laboratory, Hospital of the University of Pennsylvania, Philadelphia PA, USA
| | - Jay N Giedd
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Armin Raznahan
- Developmental Neurogenomics Unit, National Institutes of Mental Health, Bethesda, MD, USA
| | - Michael C Neale
- Department of Psychiatry and Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, PO Box 980126, Richmond, VA, USA
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48
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Vander Linden C, Verhelst H, Deschepper E, Vingerhoets G, Deblaere K, Caeyenberghs K. Cognitive training benefit depends on brain injury location in adolescents with traumatic brain injury: a pilot study. Eur J Phys Rehabil Med 2019; 55:585-594. [DOI: 10.23736/s1973-9087.18.05548-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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Horvath A, Kiss M, Szucs A, Kamondi A. Precuneus-Dominant Degeneration of Parietal Lobe Is at Risk of Epilepsy in Mild Alzheimer's Disease. Front Neurol 2019; 10:878. [PMID: 31507508 PMCID: PMC6713905 DOI: 10.3389/fneur.2019.00878] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 07/29/2019] [Indexed: 02/02/2023] Open
Abstract
Introduction: Alzheimer's disease (AD) is the leading cause of cognitive decline. Epilepsy is a frequent comorbid condition of AD. While previous studies analyzed the risk factors of AD-related epileptic seizures, we still lack biomarkers of epilepsy in mild AD cases. Purpose: The aim of our study was to analyze the correlations between neuropsychology, cortical thickness, and brain volumetric measurements in mild Alzheimer patients with concomitant epileptic seizures. Materials and methods: We selected mild AD patients from our database to examine them with structural magnetic resonance imaging, 24 h electroencephalography, and detailed neuropsychology. We made the diagnosis of epilepsy based on epileptology data including neurophysiology. We retrospectively analyzed the neuropsychology pattern, clinical and epidemiologic features, cortical thickness, and volumetric values of mild AD patients with and without overt clinical seizures using covariance weighted general linear model. Results: We found epileptic seizures in 26% of mild AD patients. Patients with seizures performed worse in visuo-spatial scores than patients without (p = 0.003). Patients with seizures had smaller parietal thickness (p = 0.018), being associated to reduced thickness of left (p = 0.007), and right precunei (p = 0.005). The visuo-spatial performance positively and strongly correlated with the thickness of the parietal lobe (r = 0.67; p = 0.002) and with the volume of the precuneus (r = 0.612; p = 0.005). Conclusion: Epileptic seizures are common even in mild AD. We found that a prominent deficit in visuo-spatial skills is a red flag for epileptic seizures in the initial phase of AD, indicating the early involvement of parietal lobe in the neurodegenerative process. Because our findings suggest that the degeneration of precuneus is a sensitive marker of seizures associated to mild AD, clinicians need to pay special attention to the pattern of atrophy shown by structural MRI. Our results confirm previous data suggesting that epileptic seizures might be associated to a faster progressing type of AD with the early degeneration of posterior cortical areas.
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Affiliation(s)
- Andras Horvath
- Department of Neurology, National Institute of Clinical Neurosciences, Budapest, Hungary.,Department of Anatomy Histology and Embryology, Semmelweis University, Budapest, Hungary
| | - Mate Kiss
- Department of Neurology, National Institute of Clinical Neurosciences, Budapest, Hungary
| | - Anna Szucs
- Department of Neurology, National Institute of Clinical Neurosciences, Budapest, Hungary
| | - Anita Kamondi
- Department of Neurology, National Institute of Clinical Neurosciences, Budapest, Hungary.,Department of Neurology, Semmelweis University, Budapest, Hungary
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Murray DW, Rosanbalm K, Christopoulos C, Meyer AL. An Applied Contextual Model for Promoting Self-Regulation Enactment Across Development: Implications for Prevention, Public Health and Future Research. J Prim Prev 2019; 40:367-403. [PMID: 31372788 DOI: 10.1007/s10935-019-00556-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
This theoretical paper presents a public health approach for promoting self-regulation across development that is based in cross-disciplinary theory and research. The self-regulation promotion model includes three key approaches that are each dependent on the relationship that children and youth have with caregivers: teaching self-regulation skills, building supportive environments, and providing co-regulation. This model extends the science of self-regulation insofar as it: (1) focuses on promoting wellbeing (not only reducing risks) across domains of functioning, (2) addresses self-regulation intervention across childhood and through young adulthood, (3) integrates multiple theories and applies them to intervention in meaningful ways, and (4) identifies specific strategies that can be used in natural developmental contexts and that address the social ecological environment as well as the individual child. We describe seven key principles that support the model including a description of self-regulation processes and implications for promoting self-regulation at each developmental stage. We end with broad implications for intervention, highlighting the relevance of the self-regulation promotion model for practitioners, policy makers, and prevention researchers.
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Affiliation(s)
- Desiree W Murray
- Frank Porter Graham Child Development Institute, University of North Carolina at Chapel Hill, Campus Box 8185, Chapel Hill, NC, 27599-8185, USA. .,The Sanford School of Public Policy, Duke University, Durham, USA.
| | - Katie Rosanbalm
- Center for Child and Family Policy, Duke University, Durham, USA
| | | | - Aleta L Meyer
- Office of Planning, Research, and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services, Washington, D.C., USA
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