1
|
Filippi CA, Winkler AM, Kanel D, Elison JT, Hardiman H, Sylvester C, Pine DS, Fox NA. Neural Correlates of Novelty-Evoked Distress in 4-Month-Old Infants: A Synthetic Cohort Study. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:905-914. [PMID: 38641209 PMCID: PMC11381178 DOI: 10.1016/j.bpsc.2024.03.008] [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: 12/08/2023] [Revised: 03/28/2024] [Accepted: 03/28/2024] [Indexed: 04/21/2024]
Abstract
BACKGROUND Observational assessments of infant temperament have provided unparalleled insight into prediction of risk for social anxiety. However, it is challenging to administer and score these assessments alongside high-quality infant neuroimaging data. In the current study, we aimed to identify infant resting-state functional connectivity associated with both parent report and observed behavioral estimates of infant novelty-evoked distress. METHODS Using data from the OIT (Origins of Infant Temperament) study, which includes deep phenotyping of infant temperament, we identified parent-report measures that were associated with observed novelty-evoked distress. These parent-report measures were then summarized into a composite score used for imaging analysis. Our infant magnetic resonance imaging sample was a synthetic cohort, harmonizing data from 2 functional magnetic resonance imaging studies of 4-month-old infants (OIT and BCP [Baby Connectome Project]; n = 101), both of which included measures of parent-reported temperament. Brain-behavior associations were evaluated using enrichment, a statistical approach that quantifies the clustering of brain-behavior associations within network pairs. RESULTS Results demonstrated that parent-report composites of novelty-evoked distress were significantly associated with 3 network pairs: dorsal attention-salience/ventral attention, dorsal attention-default mode, and dorsal attention-control. These network pairs demonstrated negative associations with novelty-evoked distress, indicating that less connectivity between these network pairs was associated with greater novelty-evoked distress. Additional analyses demonstrated that dorsal attention-control network connectivity was associated with observed novelty-evoked distress in the OIT sample (n = 38). CONCLUSIONS Overall, this work is broadly consistent with existing work and implicates dorsal attention network connectivity in novelty-evoked distress. This study provides novel data on the neural basis of infant novelty-evoked distress.
Collapse
Affiliation(s)
- Courtney A Filippi
- Department of Child and Adolescent Psychiatry, New York University Grossman School of Medicine, New York, New York.
| | - Anderson M Winkler
- Division of Human Genetics, School of Medicine, University of Texas Rio Grande Valley, Brownsville, Texas
| | - Dana Kanel
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, Maryland; Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland
| | - Jed T Elison
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, Minnesota
| | - Hannah Hardiman
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, Maryland; Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland
| | - Chad Sylvester
- Departments of Psychiatry, Radiology, and the Taylor Family Institute for Innovative Research, Washington University, St. Louis, Missouri
| | - Daniel S Pine
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, Maryland
| | - Nathan A Fox
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland
| |
Collapse
|
2
|
Kwiatkowski A, Weidler C, Habel U, Coverdale NS, Hirad AA, Manning KY, Rauscher A, Bazarian JJ, Cook DJ, Li DKB, Mahon BZ, Menon RS, Taunton J, Reetz K, Romanzetti S, Huppertz C. Uncovering the hidden effects of repetitive subconcussive head impact exposure: A mega-analytic approach characterizing seasonal brain microstructural changes in contact and collision sports athletes. Hum Brain Mapp 2024; 45:e26811. [PMID: 39185683 PMCID: PMC11345636 DOI: 10.1002/hbm.26811] [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: 01/19/2024] [Revised: 07/16/2024] [Accepted: 07/20/2024] [Indexed: 08/27/2024] Open
Abstract
Repetitive subconcussive head impacts (RSHI) are believed to induce sub-clinical brain injuries, potentially resulting in cumulative, long-term brain alterations. This study explores patterns of longitudinal brain white matter changes across sports with RSHI-exposure. A systematic literature search identified 22 datasets with longitudinal diffusion magnetic resonance imaging data. Four datasets were centrally pooled to perform uniform quality control and data preprocessing. A total of 131 non-concussed active athletes (American football, rugby, ice hockey; mean age: 20.06 ± 2.06 years) with baseline and post-season data were included. Nonparametric permutation inference (one-sample t tests, one-sided) was applied to analyze the difference maps of multiple diffusion parameters. The analyses revealed widespread lateralized patterns of sports-season-related increases and decreases in mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) across spatially distinct white matter regions. Increases were shown across one MD-cluster (3195 voxels; mean change: 2.34%), one AD-cluster (5740 voxels; mean change: 1.75%), and three RD-clusters (817 total voxels; mean change: 3.11 to 4.70%). Decreases were shown across two MD-clusters (1637 total voxels; mean change: -1.43 to -1.48%), two RD-clusters (1240 total voxels; mean change: -1.92 to -1.93%), and one AD-cluster (724 voxels; mean change: -1.28%). The resulting pattern implies the presence of strain-induced injuries in central and brainstem regions, with comparatively milder physical exercise-induced effects across frontal and superior regions of the left hemisphere, which need further investigation. This article highlights key considerations that need to be addressed in future work to enhance our understanding of the nature of observed white matter changes, improve the comparability of findings across studies, and promote data pooling initiatives to allow more detailed investigations (e.g., exploring sex- and sport-specific effects).
Collapse
Affiliation(s)
- Anna Kwiatkowski
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical FacultyRWTH Aachen UniversityAachenGermany
| | - Carmen Weidler
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical FacultyRWTH Aachen UniversityAachenGermany
| | - Ute Habel
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical FacultyRWTH Aachen UniversityAachenGermany
- Institute of Neuroscience and Medicine 10, Research Centre JülichJülichGermany
- JARA‐BRAIN Institute Brain Structure Function Relationship, Research Center Jülich and RWTH Aachen UniversityAachenGermany
| | | | - Adnan A. Hirad
- Department of SurgeryUniversity of Rochester Medical CenterRochesterNew YorkUSA
- Department of NeuroscienceUniversity of Rochester Medical CenterRochesterNew YorkUSA
- Del Monte Neuroscience Institute, University of RochesterNew YorkUSA
| | - Kathryn Y. Manning
- Department of RadiologyUniversity of Calgary and Alberta Children's Hospital Research InstituteCalgaryAlbertaCanada
| | - Alexander Rauscher
- Department of Radiology, Faculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Department of Pediatrics, Division of NeurologyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- Department of Physics and AstronomyUniversity of British ColumbiaVancouverBritish ColumbiaCanada
- UBC MRI Research Centre, University of British ColumbiaVancouverBritish ColumbiaCanada
| | - Jeffrey J. Bazarian
- Department of Emergency MedicineUniversity of Rochester School of Medicine and DentistryRochesterNew YorkUSA
| | - Douglas J. Cook
- Centre for Neuroscience Studies, Queen's UniversityKingstonOntarioCanada
- Division of Neurosurgery, Department of SurgeryQueen's UniversityKingstonOntarioCanada
| | - David K. B. Li
- Department of Radiology, Faculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Bradford Z. Mahon
- Department of PsychologyCarnegie Mellon UniversityPittsburghPennsylvaniaUSA
- Carnegie Mellon Neuroscience InstitutePittsburghPennsylvaniaUSA
- Department of NeurosurgeryUniversity of Rochester Medical CenterRochesterNew YorkUSA
| | - Ravi S. Menon
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western OntarioLondonOntarioCanada
| | - Jack Taunton
- Allan McGavin Sports Medicine Centre, Faculty of MedicineUniversity of British ColumbiaVancouverBritish ColumbiaCanada
| | - Kathrin Reetz
- Department of Neurology, Medical FacultyRWTH Aachen UniversityAachenGermany
- JARA‐BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich and RWTH Aachen UniversityAachenGermany
| | - Sandro Romanzetti
- Department of Neurology, Medical FacultyRWTH Aachen UniversityAachenGermany
- JARA‐BRAIN Institute Molecular Neuroscience and Neuroimaging, Research Center Jülich and RWTH Aachen UniversityAachenGermany
| | - Charlotte Huppertz
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical FacultyRWTH Aachen UniversityAachenGermany
| |
Collapse
|
3
|
Jahanshad N, Lenzini P, Bijsterbosch J. Current best practices and future opportunities for reproducible findings using large-scale neuroimaging in psychiatry. Neuropsychopharmacology 2024:10.1038/s41386-024-01938-8. [PMID: 39117903 DOI: 10.1038/s41386-024-01938-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Revised: 06/05/2024] [Accepted: 07/09/2024] [Indexed: 08/10/2024]
Abstract
Research into the brain basis of psychopathology is challenging due to the heterogeneity of psychiatric disorders, extensive comorbidities, underdiagnosis or overdiagnosis, multifaceted interactions with genetics and life experiences, and the highly multivariate nature of neural correlates. Therefore, increasingly larger datasets that measure more variables in larger cohorts are needed to gain insights. In this review, we present current "best practice" approaches for using existing databases, collecting and sharing new repositories for big data analyses, and future directions for big data in neuroimaging and psychiatry with an emphasis on contributing to collaborative efforts and the challenges of multi-study data analysis.
Collapse
Affiliation(s)
- Neda Jahanshad
- Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, 90292, USA.
| | - Petra Lenzini
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO, 63110, USA
| | - Janine Bijsterbosch
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO, 63110, USA.
| |
Collapse
|
4
|
Zhang X, Wu B, Yang X, Kemp GJ, Wang S, Gong Q. Abnormal large-scale brain functional network dynamics in social anxiety disorder. CNS Neurosci Ther 2024; 30:e14904. [PMID: 39107947 PMCID: PMC11303268 DOI: 10.1111/cns.14904] [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: 03/10/2024] [Revised: 07/02/2024] [Accepted: 07/25/2024] [Indexed: 08/10/2024] Open
Abstract
AIMS Although static abnormalities of functional brain networks have been observed in patients with social anxiety disorder (SAD), the brain connectome dynamics at the macroscale network level remain obscure. We therefore used a multivariate data-driven method to search for dynamic functional network connectivity (dFNC) alterations in SAD. METHODS We conducted spatial independent component analysis, and used a sliding-window approach with a k-means clustering algorithm, to characterize the recurring states of brain resting-state networks; then state transition metrics and FNC strength in the different states were compared between SAD patients and healthy controls (HC), and the relationship to SAD clinical characteristics was explored. RESULTS Four distinct recurring states were identified. Compared with HC, SAD patients demonstrated higher fractional windows and mean dwelling time in the highest-frequency State 3, representing "widely weaker" FNC, but lower in States 2 and 4, representing "locally stronger" and "widely stronger" FNC, respectively. In State 1, representing "widely moderate" FNC, SAD patients showed decreased FNC mainly between the default mode network and the attention and perceptual networks. Some aberrant dFNC signatures correlated with illness duration. CONCLUSION These aberrant patterns of brain functional synchronization dynamics among large-scale resting-state networks may provide new insights into the neuro-functional underpinnings of SAD.
Collapse
Affiliation(s)
- Xun Zhang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China HospitalSichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
| | - Baolin Wu
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China HospitalSichuan UniversityChengduChina
| | - Xun Yang
- School of Public AffairsChongqing UniversityChongqingChina
| | - Graham J. Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical SciencesUniversity of LiverpoolLiverpoolUK
| | - Song Wang
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China HospitalSichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
| | - Qiyong Gong
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China HospitalSichuan UniversityChengduChina
- Research Unit of PsychoradiologyChinese Academy of Medical SciencesChengduChina
- Department of RadiologyWest China Xiamen Hospital of Sichuan UniversityXiamenChina
| |
Collapse
|
5
|
Gao Y, Staginnus M. Cortical structure and subcortical volumes in conduct disorder: a coordinated analysis of 15 international cohorts from the ENIGMA-Antisocial Behavior Working Group. Lancet Psychiatry 2024; 11:620-632. [PMID: 39025633 DOI: 10.1016/s2215-0366(24)00187-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 06/03/2024] [Accepted: 06/04/2024] [Indexed: 07/20/2024]
Abstract
BACKGROUND Conduct disorder is associated with the highest burden of any mental disorder in childhood, yet its neurobiology remains unclear. Inconsistent findings limit our understanding of the role of brain structure alterations in conduct disorder. This study aims to identify the most robust and replicable brain structural correlates of conduct disorder. METHODS The ENIGMA-Antisocial Behavior Working Group performed a coordinated analysis of structural MRI data from 15 international cohorts. Eligibility criteria were a mean sample age of 18 years or less, with data available on sex, age, and diagnosis of conduct disorder, and at least ten participants with conduct disorder and ten typically developing participants. 3D T1-weighted MRI brain scans of all participants were pre-processed using ENIGMA-standardised protocols. We assessed group differences in cortical thickness, surface area, and subcortical volumes using general linear models, adjusting for age, sex, and total intracranial volume. Group-by-sex and group-by-age interactions, and DSM-subtype comparisons (childhood-onset vs adolescent-onset, and low vs high levels of callous-unemotional traits) were investigated. People with lived experience of conduct disorder were not involved in this study. FINDINGS We collated individual participant data from 1185 young people with conduct disorder (339 [28·6%] female and 846 [71·4%] male) and 1253 typically developing young people (446 [35·6%] female and 807 [64·4%] male), with a mean age of 13·5 years (SD 3·0; range 7-21). Information on race and ethnicity was not available. Relative to typically developing young people, the conduct disorder group had lower surface area in 26 cortical regions and lower total surface area (Cohen's d 0·09-0·26). Cortical thickness differed in the caudal anterior cingulate cortex (d 0·16) and the banks of the superior temporal sulcus (d -0·13). The conduct disorder group also had smaller amygdala (d 0·13), nucleus accumbens (d 0·11), thalamus (d 0·14), and hippocampus (d 0·12) volumes. Most differences remained significant after adjusting for ADHD comorbidity or intelligence quotient. No group-by-sex or group-by-age interactions were detected. Few differences were found between DSM-defined conduct disorder subtypes. However, individuals with high callous-unemotional traits showed more widespread differences compared with controls than those with low callous-unemotional traits. INTERPRETATION Our findings provide robust evidence of subtle yet widespread brain structural alterations in conduct disorder across subtypes and sexes, mostly in surface area. These findings provide further evidence that brain alterations might contribute to conduct disorder. Greater consideration of this under-recognised disorder is needed in research and clinical practice. FUNDING Academy of Medical Sciences and Economic and Social Research Council.
Collapse
Affiliation(s)
- Yidian Gao
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK
| | | |
Collapse
|
6
|
Gao C, Yang Q, Kim ME, Khairi NM, Cai LY, Newlin NR, Kanakaraj P, Remedios LW, Krishnan AR, Yu X, Yao T, Zhang P, Schilling KG, Moyer D, Archer DB, Resnick SM, Landman BA. Characterizing patterns of diffusion tensor imaging variance in aging brains. J Med Imaging (Bellingham) 2024; 11:044007. [PMID: 39185477 PMCID: PMC11344569 DOI: 10.1117/1.jmi.11.4.044007] [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: 03/11/2024] [Revised: 07/26/2024] [Accepted: 07/30/2024] [Indexed: 08/27/2024] Open
Abstract
Purpose As large analyses merge data across sites, a deeper understanding of variance in statistical assessment across the sources of data becomes critical for valid analyses. Diffusion tensor imaging (DTI) exhibits spatially varying and correlated noise, so care must be taken with distributional assumptions. Here, we characterize the role of physiology, subject compliance, and the interaction of the subject with the scanner in the understanding of DTI variability, as modeled in the spatial variance of derived metrics in homogeneous regions. Approach We analyze DTI data from 1035 subjects in the Baltimore Longitudinal Study of Aging, with ages ranging from 22.4 to 103 years old. For each subject, up to 12 longitudinal sessions were conducted. We assess the variance of DTI scalars within regions of interest (ROIs) defined by four segmentation methods and investigate the relationships between the variance and covariates, including baseline age, time from the baseline (referred to as "interval"), motion, sex, and whether it is the first scan or the second scan in the session. Results Covariate effects are heterogeneous and bilaterally symmetric across ROIs. Inter-session interval is positively related ( p ≪ 0.001 ) to FA variance in the cuneus and occipital gyrus, but negatively ( p ≪ 0.001 ) in the caudate nucleus. Males show significantly ( p ≪ 0.001 ) higher FA variance in the right putamen, thalamus, body of the corpus callosum, and cingulate gyrus. In 62 out of 176 ROIs defined by the Eve type-1 atlas, an increase in motion is associated ( p < 0.05 ) with a decrease in FA variance. Head motion increases during the rescan of DTI ( Δ μ = 0.045 mm per volume). Conclusions The effects of each covariate on DTI variance and their relationships across ROIs are complex. Ultimately, we encourage researchers to include estimates of variance when sharing data and consider models of heteroscedasticity in analysis. This work provides a foundation for study planning to account for regional variations in metric variance.
Collapse
Affiliation(s)
- Chenyu Gao
- Vanderbilt University, Department of Electrical and Computer Engineering, Nashville, Tennessee, United States
| | - Qi Yang
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Michael E. Kim
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Nazirah Mohd Khairi
- Vanderbilt University, Department of Electrical and Computer Engineering, Nashville, Tennessee, United States
| | - Leon Y. Cai
- Vanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States
| | - Nancy R. Newlin
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Praitayini Kanakaraj
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Lucas W. Remedios
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Aravind R. Krishnan
- Vanderbilt University, Department of Electrical and Computer Engineering, Nashville, Tennessee, United States
| | - Xin Yu
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Tianyuan Yao
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Panpan Zhang
- Vanderbilt University Medical Center, Department of Biostatistics, Nashville, Tennessee, United States
| | - Kurt G. Schilling
- Vanderbilt University Medical Center, Department of Radiology and Radiological Sciences, Nashville, Tennessee, United States
- Vanderbilt University, Vanderbilt University Institute of Imaging Science, Nashville, Tennessee, United States
| | - Daniel Moyer
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
| | - Derek B. Archer
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University School of Medicine, Nashville, Tennessee, United States
- Vanderbilt University Medical Center, Vanderbilt Genetics Institute, Nashville, Tennessee, United States
| | - Susan M. Resnick
- National Institute on Aging, Laboratory of Behavioral Neuroscience, Baltimore, Maryland, United States
| | - Bennett A. Landman
- Vanderbilt University, Department of Electrical and Computer Engineering, Nashville, Tennessee, United States
- Vanderbilt University, Department of Computer Science, Nashville, Tennessee, United States
- Vanderbilt University, Department of Biomedical Engineering, Nashville, Tennessee, United States
- Vanderbilt University Medical Center, Department of Radiology and Radiological Sciences, Nashville, Tennessee, United States
- Vanderbilt University, Vanderbilt University Institute of Imaging Science, Nashville, Tennessee, United States
| | | | | |
Collapse
|
7
|
Grevet LT, Teixeira DS, Pan PM, Jackowski AP, Zugman A, Miguel EC, Rohde LA, Salum GA. The association between duration of breastfeeding and the trajectory of brain development from childhood to young adulthood: an 8-year longitudinal study. Eur Child Adolesc Psychiatry 2024; 33:1863-1873. [PMID: 37650992 DOI: 10.1007/s00787-023-02283-9] [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: 03/26/2023] [Accepted: 08/14/2023] [Indexed: 09/01/2023]
Abstract
Breastfeeding has been associated with several short- and long-term health benefits, including positive cognitive and behavioral outcomes. However, the impact of breastfeeding on structural brain development over time remains unclear. We aimed to assess the association between breastfeeding duration in childhood and the developmental trajectory of overall cortical thickness, cortical area, and total intracranial volume during the transition from childhood to early adulthood. Participants included 670 children and adolescents with 1326 MRI scans acquired over 8 years from the Brazilian High-Risk Cohort for Mental Conditions (BHRCS). Breastfeeding was assessed using a questionnaire answered by the parents. Brain measures were estimated using MRI T1-weighted images at three time points, with 3-year intervals. Data were evaluated using generalized additive models adjusted for multiple confounders. We found that a longer breastfeeding duration was directly associated with higher global cortical thickness in the left (edf = 1.0, F = 6.07, p = 0.01) and right (edf = 1.0, F = 4.70, p = 0.03) hemispheres. For the total intracranial volume, we found an interaction between duration of breastfeeding and developmental stage (edf = 1.0, F = 6.81, p = 0.009). No association was found between breastfeeding duration and brain area. Our study suggests that the duration of breastfeeding impacts overall cortical thickness and the development of total brain volume, but not area. This study adds to the evidence on the potential impact of breastfeeding on brain development and provides relevant insights into the mechanisms by which breastfeeding might confer cognitive and mental health benefits.
Collapse
Affiliation(s)
- Laura Tietzmann Grevet
- Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), School of Medicine, Avenida Ipiranga, 6681-Partenon, Porto Alegre, Rio Grande do Sul, 90619-900, Brazil.
| | - Danielle Soares Teixeira
- Hospital de Clínicas de Porto Alegre (HCPA), Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil
| | - Pedro Mario Pan
- National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq), São Paulo, SP, Brazil
- Universidade Federal de São Paulo (UNIFESP), Iterdisciplinary Lab for Clinical Neurosciences (LiNC), São Paulo, SP, Brazil
| | - Andrea Parolin Jackowski
- National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq), São Paulo, SP, Brazil
- Universidade Federal de São Paulo (UNIFESP), Iterdisciplinary Lab for Clinical Neurosciences (LiNC), São Paulo, SP, Brazil
| | - André Zugman
- National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq), São Paulo, SP, Brazil
- Universidade Federal de São Paulo (UNIFESP), Iterdisciplinary Lab for Clinical Neurosciences (LiNC), São Paulo, SP, Brazil
| | - Euripedes Constantino Miguel
- National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq), São Paulo, SP, Brazil
- Department and Institute of Psychiatry, Universidade de São Paulo (USP), São Paulo, SP, Brazil
| | - Luis Augusto Rohde
- National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq), São Paulo, SP, Brazil
- ADHD Outpatient Program and Developmental Psychiatry Program, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Giovanni Abrahão Salum
- National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq), São Paulo, SP, Brazil
- Child Mind Institute, New York, NY, USA
| |
Collapse
|
8
|
Amsterdam JD, Xu C. Multi-trial, aggregated, individual participant data mega-analysis of short-term antidepressant versus mood stabilizer monotherapy of bipolar type II major depressive episode. Bipolar Disord 2024; 26:255-264. [PMID: 37749069 DOI: 10.1111/bdi.13378] [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] [Indexed: 09/27/2023]
Abstract
BACKGROUND Few studies have systematically examined the safety and effectiveness of antidepressant versus mood stabilizer monotherapy of bipolar II depression. To date, there are no aggregated or mega-analyses of prospective trials of individual participant-level data (IPD) to inform future treatment guidelines on the relative safety and effectiveness of antidepressant or lithium monotherapy. METHODS Data from a series of four independent, similarly designed trials of antidepressant or lithium monotherapy (where longitudinal IPD were available) (n = 393) were aggregated into an IPD dataset (i.e., mega-analysis). Hierarchical log-linear growth models were used to analyze primary outcome of change over time in Hamilton Rating Scale for Depression (HRSD) scores; while secondary outcomes examined Clinical Global Impressions severity (CGI/S) and change (CGI/C) scores, and change over time in Young Mania Rating (YMR) scores. RESULTS Relative to lithium monotherapy, antidepressant monotherapy demonstrated significantly greater symptom reduction on HRSD scores across time (b = -2.33, t = -6.68, p < 0.0001), significantly greater symptom reduction on the CGI/S across time (b = -0.414, t = -6.32, p < 0.001), and a significant improvement in CGI/C across time (b = -0.47, t = -7.43, p < 0.0001). No differences were observed in change over time for YMR scores between antidepressant and lithium monotherapy (b = 0.06, t = 0.49, p = 0.62). CONCLUSION Findings from this IPD mega-analysis of bipolar II depression trials suggest a divergence from current evidence-based guidelines recommending combined mood stabilizer plus antidepressant therapy. The current mega-analysis suggests that antidepressant monotherapy may provide superior short-term effectiveness without clinically meaningful increase in treatment-emergent hypomanic symptoms compared to lithium monotherapy.
Collapse
Affiliation(s)
- Jay D Amsterdam
- Depression Research Unit, Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Colin Xu
- Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| |
Collapse
|
9
|
Liu H, Hao Z, Qiu S, Wang Q, Zhan L, Huang L, Shao Y, Wang Q, Su C, Cao Y, Sun J, Wang C, Lv Y, Li M, Shen W, Li H, Jia X. Grey matter structural alterations in anxiety disorders: a voxel-based meta-analysis. Brain Imaging Behav 2024; 18:456-474. [PMID: 38150133 DOI: 10.1007/s11682-023-00842-x] [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] [Accepted: 12/07/2023] [Indexed: 12/28/2023]
Abstract
Anxiety disorders (ADs) are a group of prevalent and destructive mental illnesses, but the current understanding of their underlying neuropathology is still unclear. Employing voxel-based morphometry (VBM), previous studies have demonstrated several common brain regions showing grey matter volume (GMV) abnormalities. However, contradictory results have been reported among these studies. Considering that different subtypes of ADs exhibit common core symptoms despite different diagnostic criteria, and previous meta-analyses have found common core GMV-altered brain regions in ADs, the present research aimed to combine the results of individual studies to identify common GMV abnormalities in ADs. Therefore, we first performed a systematic search in PubMed, Embase, and Web of Science on studies investigating GMV differences between patients with ADs and healthy controls (HCs). Then, the anisotropic effect-size signed differential mapping (AES-SDM) was applied in this meta-analysis. A total of 24 studies (including 25 data sets) were included in the current study, and 906 patients with ADs and 1003 HCs were included. Compared with the HCs, the patients with ADs showed increased GMV in the left superior parietal gyrus, right angular gyrus, left precentral gyrus, and right lingual gyrus, and decreased GMV in the bilateral insula, bilateral thalamus, left caudate, and right putamen. In conclusion, the current study has identified some abnormal GMV brain regions that are related to the pathological mechanisms of anxiety disorders. These findings could contribute to a better understanding of the underlying neuropathology of ADs.
Collapse
Affiliation(s)
- Han Liu
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Zeqi Hao
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Shasha Qiu
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Qianqian Wang
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Linlin Zhan
- School of Western Languages, Heilongjiang University, Heilongjiang, China
| | - Lina Huang
- Department of Radiology, Changshu No.2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
| | - Youbin Shao
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Qing Wang
- Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian, China
| | - Chang Su
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Yikang Cao
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Jiawei Sun
- School of Information and Electronics Technology, Jiamusi University, Jiamusi, China
| | - Chunjie Wang
- Institute of Brain Science, Department of Psychology, School of Education, Hangzhou Normal University, Hangzhou, China
- Center for Cognition and Brain Disorders, the Affiliated Hospital, Hangzhou Normal University, Hangzhou, China
| | - Yating Lv
- Center for Cognition and Brain Disorders, the Affiliated Hospital, Hangzhou Normal University, Hangzhou, China
| | - Mengting Li
- School of Psychology, Zhejiang Normal University, Jinhua, China
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China
| | - Wenbin Shen
- Department of Radiology, Changshu No.2 People's Hospital, The Affiliated Changshu Hospital of Xuzhou Medical University, Changshu, Jiangsu, China
| | - Huayun Li
- School of Psychology, Zhejiang Normal University, Jinhua, China.
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China.
| | - Xize Jia
- School of Psychology, Zhejiang Normal University, Jinhua, China.
- Intelligent Laboratory of Zhejiang Province in Mental Health and Crisis Intervention for Children and Adolescents, Zhejiang Normal University, Jinhua, China.
| |
Collapse
|
10
|
Keeler JL, Bahnsen K, Wronski ML, Bernardoni F, Tam F, Arold D, King JA, Kolb T, Poitz DM, Roessner V, Treasure J, Himmerich H, Ehrlich S. Longitudinal changes in brain-derived neurotrophic factor (BDNF) but not cytokines contribute to hippocampal recovery in anorexia nervosa above increases in body mass index. Psychol Med 2024:1-12. [PMID: 38450444 DOI: 10.1017/s0033291724000394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
BACKGROUND Physical sequelae of anorexia nervosa (AN) include a marked reduction in whole brain volume and subcortical structures such as the hippocampus. Previous research has indicated aberrant levels of inflammatory markers and growth factors in AN, which in other populations have been shown to influence hippocampal integrity. METHODS Here we investigated the influence of concentrations of two pro-inflammatory cytokines (tumor necrosis factor-alpha [TNF-α] and interleukin-6 [IL-6]) and brain-derived neurotrophic factor (BDNF) on the whole hippocampal volume, as well as the volumes of three regions (the hippocampal body, head, and tail) and 18 subfields bilaterally. Investigations occurred both cross-sectionally between acutely underweight adolescent/young adult females with AN (acAN; n = 82) and people recovered from AN (recAN; n = 20), each independently pairwise age-matched with healthy controls (HC), and longitudinally in acAN after partial renourishment (n = 58). Hippocampal subfield volumes were quantified using FreeSurfer. Concentrations of molecular factors were analyzed in linear models with hippocampal (subfield) volumes as the dependent variable. RESULTS Cross-sectionally, there was no evidence for an association between IL-6, TNF-α, or BDNF and between-group differences in hippocampal subfield volumes. Longitudinally, increasing concentrations of BDNF were positively associated with longitudinal increases in bilateral global hippocampal volumes after controlling for age, age2, estimated total intracranial volume, and increases in body mass index (BMI). CONCLUSIONS These findings suggest that increases in BDNF may contribute to global hippocampal recovery over and above increases in BMI during renourishment. Investigations into treatments targeted toward increasing BDNF in AN may be warranted.
Collapse
Affiliation(s)
- Johanna Louise Keeler
- Centre for Research in Eating and Weight Disorders (CREW), Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Klaas Bahnsen
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Marie-Louis Wronski
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
- Neuroendocrine Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Fabio Bernardoni
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Friederike Tam
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
- Eating Disorder Treatment and Research Center, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Dominic Arold
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Joseph A King
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Theresa Kolb
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - David M Poitz
- Institute for Clinical Chemistry and Laboratory Medicine, TU Dresden, Dresden, Germany
| | - Veit Roessner
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Janet Treasure
- Centre for Research in Eating and Weight Disorders (CREW), Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Hubertus Himmerich
- Centre for Research in Eating and Weight Disorders (CREW), Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
- Eating Disorder Treatment and Research Center, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany
| |
Collapse
|
11
|
Bahnsen K, Wronski ML, Keeler JL, King JA, Preusker Q, Kolb T, Weidner K, Roessner V, Bernardoni F, Ehrlich S. Differential longitudinal changes of hippocampal subfields in patients with anorexia nervosa. Psychiatry Clin Neurosci 2024; 78:186-196. [PMID: 38018338 DOI: 10.1111/pcn.13626] [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: 08/11/2023] [Revised: 10/31/2023] [Accepted: 11/26/2023] [Indexed: 11/30/2023]
Abstract
BACKGROUND Anorexia nervosa (AN) is a mental disorder characterized by dietary restriction, fear of gaining weight, and distorted body image. Recent studies indicate that the hippocampus, crucial for learning and memory, may be affected in AN, yet subfield-specific effects remain unclear. We investigated hippocampal subfield alterations in acute AN, changes following weight restoration, and their associations with leptin levels. METHODS T1-weighted magnetic resonance imaging scans were processed using FreeSurfer. We compared 22 left and right hemispheric hippocampal subfield volumes cross-sectionally and longitudinally in females with acute AN (n = 165 at baseline, n = 110 after partial weight restoration), healthy female controls (HCs; n = 271), and females after long-term recovery from AN (n = 79) using linear models. RESULTS We found that most hippocampal subfield volumes were significantly reduced in patients with AN compared with HCs (~-3.9%). Certain areas such as the subiculum exhibited no significant reduction in the acute state of AN, while other areas, such as the hippocampal tail, showed strong decreases (~-9%). Following short-term weight recovery, most subfields increased in volume. Comparisons between participants after long-term weight-recovery and HC yielded no differences. The hippocampal tail volume was positively associated with leptin levels in AN independent of body mass index. CONCLUSIONS Our study provides evidence of differential volumetric differences in hippocampal subfields between individuals with AN and HC and almost complete normalization after weight rehabilitation. These alterations are spatially inhomogeneous and more pronounced compared with other major mental disorders (e.g. major depressive disorder and schizophrenia). We provide novel insights linking hypoleptinemia to hippocampal subfield alterations hinting towards clinical relevance of leptin normalization in AN recovery.
Collapse
Affiliation(s)
- Klaas Bahnsen
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Marie-Louis Wronski
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
- Neuroendocrine Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Johanna Louise Keeler
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
- Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Joseph A King
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Quirina Preusker
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Theresa Kolb
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Kerstin Weidner
- Department of Psychotherapy and Psychosomatic Medicine, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Veit Roessner
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Fabio Bernardoni
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
- Eating Disorder Research and Treatment Center, Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| |
Collapse
|
12
|
Hoffmann MS, Moore TM, Axelrud LK, Tottenham N, Pan PM, Miguel EC, Rohde LA, Milham MP, Satterthwaite TD, Salum GA. An Evaluation of Item Harmonization Strategies Between Assessment Tools of Psychopathology in Children and Adolescents. Assessment 2024; 31:502-517. [PMID: 37042304 DOI: 10.1177/10731911231163136] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2023]
Abstract
Data aggregation in mental health is complicated by using different questionnaires, and little is known about the impact of item harmonization strategies on measurement precision. Therefore, we aimed to assess the impact of various item harmonization strategies for a target and proxy questionnaire using correlated and bifactor models. Data were obtained from the Brazilian High-Risk Study for Mental Conditions (BHRCS) and the Healthy Brain Network (HBN; N = 6,140, ages 5-22 years, 39.6% females). We tested six item-wise harmonization strategies and compared them based on several indices. The one-by-one (1:1) expert-based semantic item harmonization presented the best strategy as it was the only that resulted in scalar-invariant models for both samples and factor models. The between-questionnaires factor correlation, reliability, and factor score difference in using a proxy instead of a target measure improved little when all other harmonization strategies were compared with a completely at-random strategy. However, for bifactor models, between-questionnaire specific factor correlation increased from 0.05-0.19 (random item harmonization) to 0.43-0.60 (expert-based 1:1 semantic harmonization) in BHRCS and HBN samples, respectively. Therefore, item harmonization strategies are relevant for specific factors from bifactor models and had little impact on p-factors and first-order correlated factors when the child behavior checklist (CBCL) and strengths and difficulties questionnaire (SDQ) were harmonized.
Collapse
Affiliation(s)
- Maurício Scopel Hoffmann
- Universidade Federal de Santa Maria, Brazil
- Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- London School of Economics and Political Science, UK
| | | | | | | | - Pedro Mario Pan
- Universidade Federal de São Paulo, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq), São Paulo, Brazil
| | - Eurípedes Constantino Miguel
- National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq), São Paulo, Brazil
- Universidade de São Paulo, Brazil
| | - Luis Augusto Rohde
- Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq), São Paulo, Brazil
| | - Michael Peter Milham
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Child Mind Institute, New York, NY, USA
| | | | - Giovanni Abrahão Salum
- Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq), São Paulo, Brazil
- Child Mind Institute, New York, NY, USA
| |
Collapse
|
13
|
Zugman A, Winkler AM, Qamar P, Pine DS. Current and Future Approaches to Pediatric Anxiety Disorder Treatment. Am J Psychiatry 2024; 181:189-200. [PMID: 38425255 PMCID: PMC11256210 DOI: 10.1176/appi.ajp.20231037] [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] [Indexed: 03/02/2024]
Abstract
This overview critically appraises the literature on the treatment of pediatric anxiety disorders. The two established treatments for these conditions comprise cognitive-behavioral therapy (CBT) and antidepressant medications. Many youths receiving these treatments fail to achieve remission, which creates a need for new treatments. After summarizing the literature on CBT and currently available medications, the authors describe research that lays a foundation for improvements in the treatment of pediatric anxiety disorders. This foundation leverages neuroscientific investigations, also described in the overview, which provide insights on mechanisms of successful treatment.
Collapse
Affiliation(s)
- Andre Zugman
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch (EDB), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, United States
| | - Anderson M. Winkler
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch (EDB), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, United States
- Division of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, Texas, United States
| | - Purnima Qamar
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch (EDB), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, United States
| | - Daniel S. Pine
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch (EDB), National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland, United States
| |
Collapse
|
14
|
Cardoner N, Andero R, Cano M, Marin-Blasco I, Porta-Casteràs D, Serra-Blasco M, Via E, Vicent-Gil M, Portella MJ. Impact of Stress on Brain Morphology: Insights into Structural Biomarkers of Stress-related Disorders. Curr Neuropharmacol 2024; 22:935-962. [PMID: 37403395 PMCID: PMC10845094 DOI: 10.2174/1570159x21666230703091435] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/04/2023] [Accepted: 01/23/2023] [Indexed: 07/06/2023] Open
Abstract
Exposure to acute and chronic stress has a broad range of structural effects on the brain. The brain areas commonly targeted in the stress response models include the hippocampus, the amygdala, and the prefrontal cortex. Studies in patients suffering from the so-called stress-related disorders -embracing post-traumatic stress, major depressive and anxiety disorders- have fairly replicated animal models of stress response -particularly the neuroendocrine and the inflammatory models- by finding alterations in different brain areas, even in the early neurodevelopment. Therefore, this narrative review aims to provide an overview of structural neuroimaging findings and to discuss how these studies have contributed to our knowledge of variability in response to stress and the ulterior development of stress-related disorders. There are a gross number of studies available but neuroimaging research of stress-related disorders as a single category is still in its infancy. Although the available studies point at particular brain circuitries involved in stress and emotion regulation, the pathophysiology of these abnormalities -involving genetics, epigenetics and molecular pathways-, their relation to intraindividual stress responses -including personality characteristics, self-perception of stress conditions…-, and their potential involvement as biomarkers in diagnosis, treatment prescription and prognosis are discussed.
Collapse
Affiliation(s)
- Narcís Cardoner
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, School of Medicine Bellaterra, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
| | - Raül Andero
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
- Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
- Departament de Psicobiologia i de Metodologia de les Ciències de la Salut, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
- ICREA, Barcelona, Spain
| | - Marta Cano
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Ignacio Marin-Blasco
- Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Barcelona, Spain
| | - Daniel Porta-Casteràs
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, School of Medicine Bellaterra, Universitat Autònoma de Barcelona, Barcelona, Spain
- Unitat de Neurociència Traslacional, Parc Taulí Hospital Universitari, Institut d'Investigació i Innovació Parc Taulí (I3PT), Institut de Neurociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
| | - Maria Serra-Blasco
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Programa eHealth ICOnnecta't, Institut Català d'Oncologia, Barcelona, Spain
| | - Esther Via
- Child and Adolescent Psychiatry and Psychology Department, Hospital Sant Joan de Déu, Barcelona, Spain
- Child and Adolescent Mental Health Research Group, Institut de Recerca Sant Joan de Déu, Barcelona, Spain
| | - Muriel Vicent-Gil
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Maria J. Portella
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, School of Medicine Bellaterra, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica En Red en Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| |
Collapse
|
15
|
Kępińska AP, Johnson JS, Huckins LM. Open Science Practices in Psychiatric Genetics: A Primer. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:110-119. [PMID: 38298792 PMCID: PMC10829621 DOI: 10.1016/j.bpsgos.2023.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 08/04/2023] [Accepted: 08/11/2023] [Indexed: 02/02/2024] Open
Abstract
Open science ensures that research is transparently reported and freely accessible for all to assess and collaboratively build on. Psychiatric genetics has led among the health sciences in implementing some open science practices in common study designs, such as replication as part of genome-wide association studies. However, thorough open science implementation guidelines are limited and largely not specific to data, privacy, and research conduct challenges in psychiatric genetics. Here, we present a primer of open science practices, including selection of a research topic with patients/nonacademic collaborators, equitable authorship and citation practices, design of replicable, reproducible studies, preregistrations, open data, and privacy issues. We provide tips for informative figures and inclusive, precise reporting. We discuss considerations in working with nonacademic collaborators and distributing research through preprints, blogs, social media, and accessible lecture materials. Finally, we provide extra resources to support every step of the research process.
Collapse
Affiliation(s)
- Adrianna P. Kępińska
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Jessica S. Johnson
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, New York
- Psychiatry Department, The University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina
| | - Laura M. Huckins
- Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
- Department of Psychiatry, Yale University, New Haven, Connecticut
| |
Collapse
|
16
|
Zhang X, Yang X, Wu B, Pan N, He M, Wang S, Kemp GJ, Gong Q. Large-scale brain functional network abnormalities in social anxiety disorder. Psychol Med 2023; 53:6194-6204. [PMID: 36330833 PMCID: PMC10520603 DOI: 10.1017/s0033291722003439] [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: 06/01/2022] [Revised: 09/06/2022] [Accepted: 10/11/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Although aberrant brain regional responses are reported in social anxiety disorder (SAD), little is known about resting-state functional connectivity at the macroscale network level. This study aims to identify functional network abnormalities using a multivariate data-driven method in a relatively large and homogenous sample of SAD patients, and assess their potential diagnostic value. METHODS Forty-six SAD patients and 52 demographically-matched healthy controls (HC) were recruited to undergo clinical evaluation and resting-state functional MRI scanning. We used group independent component analysis to characterize the functional architecture of brain resting-state networks (RSNs) and investigate between-group differences in intra-/inter-network functional network connectivity (FNC). Furtherly, we explored the associations of FNC abnormalities with clinical characteristics, and assessed their ability to discriminate SAD from HC using support vector machine analyses. RESULTS SAD patients showed widespread intra-network FNC abnormalities in the default mode network, the subcortical network and the perceptual system (i.e. sensorimotor, auditory and visual networks), and large-scale inter-network FNC abnormalities among those high-order and primary RSNs. Some aberrant FNC signatures were correlated to disease severity and duration, suggesting pathophysiological relevance. Furthermore, intrinsic FNC anomalies allowed individual classification of SAD v. HC with significant accuracy, indicating potential diagnostic efficacy. CONCLUSIONS SAD patients show distinct patterns of functional synchronization abnormalities both within and across large-scale RSNs, reflecting or causing a network imbalance of bottom-up response and top-down regulation in cognitive, emotional and sensory domains. Therefore, this could offer insights into the neurofunctional substrates of SAD.
Collapse
Affiliation(s)
- Xun Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan 610041, China
| | - Xun Yang
- School of Public Affairs, Chongqing University, Chongqing 400044, China
| | - Baolin Wu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan 610041, China
| | - Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan 610041, China
| | - Min He
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan 610041, China
| | - Song Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan 610041, China
| | - Graham J. Kemp
- Liverpool Magnetic Resonance Imaging Centre (LiMRIC) and Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L69 3BX, UK
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan 610041, China
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian 361000, China
| |
Collapse
|
17
|
Zugman A, Jett L, Antonacci C, Winkler AM, Pine DS. A systematic review and meta-analysis of resting-state fMRI in anxiety disorders: Need for data sharing to move the field forward. J Anxiety Disord 2023; 99:102773. [PMID: 37741177 PMCID: PMC10753861 DOI: 10.1016/j.janxdis.2023.102773] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 09/11/2023] [Accepted: 09/12/2023] [Indexed: 09/25/2023]
Abstract
Anxiety disorders are among the most prevalent psychiatric disorders. Neuroimaging findings remain uncertain, and resting state functional magnetic resonance (rs-fMRI) connectivity is of particular interest since it is a scalable functional imaging modality. Given heterogeneous past findings for rs-fMRI in anxious individuals, we characterize patterns across anxiety disorders by conducting a systematic review and meta-analysis. Studies were included if they contained at the time of scanning both a healthy group and a patient group. Due to insufficient study numbers, the quantitative meta-analysis only included seed-based studies. We performed an activation likelihood estimation (ALE) analysis that compared patients and healthy volunteers. All analyses were corrected for family-wise error with a cluster-level threshold of p < .05. Patients exhibited hypo-connectivity between the amygdala and the medial frontal gyrus, anterior cingulate cortex, and cingulate gyrus. This finding, however, was not robust to potential file-drawer effects. Though limited by strict inclusion criteria, our results highlight the heterogeneous nature of reported findings. This underscores the need for data sharing when attempting to detect reliable patterns of disruption in brain activity across anxiety disorders.
Collapse
Affiliation(s)
- André Zugman
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
| | - Laura Jett
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States; Child Emotion Lab, University of Wisconsin, Madison, Madison, WI, United States.
| | - Chase Antonacci
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States; Department of Psychology, Stanford University, Stanford, CA, United States.
| | - Anderson M Winkler
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States; Division of Human Genetics, School of Medicine, The University of Texas Rio Grande Valley, Brownsville, Texas, United States.
| | - Daniel S Pine
- Section on Development and Affective Neuroscience (SDAN), Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States.
| |
Collapse
|
18
|
Banaj N, Vecchio D, Piras F, De Rossi P, Bustillo J, Ciufolini S, Dazzan P, Di Forti M, Dickie EW, Ford JM, Fuentes-Claramonte P, Gruber O, Guerrero-Pedraza A, Hamilton HK, Howells FM, Kraemer B, Lawrie SM, Mathalon DH, Murray R, Pomarol-Clotet E, Potkin SG, Preda A, Radua J, Richter A, Salvador R, Sawa A, Scheffler F, Sim K, Spaniel F, Stein DJ, Temmingh HS, Thomopoulos SI, Tomecek D, Uhlmann A, Voineskos A, Yang K, Jahanshad N, Thompson PM, Van Erp TGM, Turner JA, Spalletta G, Piras F. Cortical morphology in patients with the deficit and non-deficit syndrome of schizophrenia: a worldwide meta- and mega-analyses. Mol Psychiatry 2023; 28:4363-4373. [PMID: 37644174 PMCID: PMC10827665 DOI: 10.1038/s41380-023-02221-w] [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: 01/20/2023] [Revised: 08/02/2023] [Accepted: 08/07/2023] [Indexed: 08/31/2023]
Abstract
Converging evidence suggests that schizophrenia (SZ) with primary, enduring negative symptoms (i.e., Deficit SZ (DSZ)) represents a distinct entity within the SZ spectrum while the neurobiological underpinnings remain undetermined. In the largest dataset of DSZ and Non-Deficit (NDSZ), we conducted a meta-analysis of data from 1560 individuals (168 DSZ, 373 NDSZ, 1019 Healthy Controls (HC)) and a mega-analysis of a subsampled data from 944 individuals (115 DSZ, 254 NDSZ, 575 HC) collected across 9 worldwide research centers of the ENIGMA SZ Working Group (8 in the mega-analysis), to clarify whether they differ in terms of cortical morphology. In the meta-analysis, sites computed effect sizes for differences in cortical thickness and surface area between SZ and control groups using a harmonized pipeline. In the mega-analysis, cortical values of individuals with schizophrenia and control participants were analyzed across sites using mixed-model ANCOVAs. The meta-analysis of cortical thickness showed a converging pattern of widespread thinner cortex in fronto-parietal regions of the left hemisphere in both DSZ and NDSZ, when compared to HC. However, DSZ have more pronounced thickness abnormalities than NDSZ, mostly involving the right fronto-parietal cortices. As for surface area, NDSZ showed differences in fronto-parietal-temporo-occipital cortices as compared to HC, and in temporo-occipital cortices as compared to DSZ. Although DSZ and NDSZ show widespread overlapping regions of thinner cortex as compared to HC, cortical thinning seems to better typify DSZ, being more extensive and bilateral, while surface area alterations are more evident in NDSZ. Our findings demonstrate for the first time that DSZ and NDSZ are characterized by different neuroimaging phenotypes, supporting a nosological distinction between DSZ and NDSZ and point toward the separate disease hypothesis.
Collapse
Affiliation(s)
- Nerisa Banaj
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy.
| | - Daniela Vecchio
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Pietro De Rossi
- Child and Adolescence Neuropsychiatry Unit, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy
| | - Juan Bustillo
- Psichiatry and Neuroscience, University of New Mexico, Albuquerque, NM, USA
| | - Simone Ciufolini
- Psychosis Studies, Institute of Psychiatry, Psychology and Neurology, King's College London, London, UK
| | - Paola Dazzan
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neurology, King's College London, London, UK
| | - Marta Di Forti
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neurology, King's College London, London, UK
| | - Erin W Dickie
- Center for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Kimel Family Lab, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Judith M Ford
- San Francisco VA Health Care System, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Paola Fuentes-Claramonte
- FIMDAG Sisters Hospitallers Research Foundation, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Baden-Wuerttemberg, Germany
| | | | - Holly K Hamilton
- San Francisco VA Health Care System, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Fleur M Howells
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, Western Cape, South Africa
| | - Bernd Kraemer
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Baden-Wuerttemberg, Germany
| | - Stephen M Lawrie
- Division of Psychiatry, University of Edinburgh, Edinburg, EH10 5HF, UK
| | - Daniel H Mathalon
- San Francisco VA Health Care System, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Robin Murray
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neurology, King's College London, London, UK
| | - Edith Pomarol-Clotet
- FIMDAG Sisters Hospitallers Research Foundation, Barcelona, Spain
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
| | - Steven G Potkin
- Department of Psychiatry, University of California Irvine, Newfoundland, NJ, NJ 07435, USA
| | - Adrian Preda
- Psychiatry and Human Behavior, University of California Irvine, Orange, CA, 92868, USA
| | - Joaquim Radua
- Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain
- Imaging of mood- and anxiety-related disorders (IMARD), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, 08036, Spain
- Medicina, University of Barcelona, Barcelona, 08036, Spain
| | - Anja Richter
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Heidelberg, Baden-Wuerttemberg, Germany
| | - Raymond Salvador
- FIMDAG Sisters Hospitallers Research Foundation, Barcelona, Spain
| | - Akira Sawa
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Genetic Medicine, Johns Hopkins University School of Medicine Baltimore, Baltimore, MD, USA
- Department of Pharmacology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Freda Scheffler
- Department of Psychiatry and Mental Health, Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Brain Behavior Unit, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Kang Sim
- West Region, Institute of Mental Health, National Healthcare Group, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Filip Spaniel
- CARE, National Institute of Mental Health, Klecany, Czech Republic
| | - Dan J Stein
- SAMRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Henk S Temmingh
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, Western Cape, South Africa
- Department of Psychiatry and Mental Health, Valkenberg Psychiatric Hospital, Cape Town, Western Cape, South Africa
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - David Tomecek
- CARE, National Institute of Mental Health, Klecany, Czech Republic
| | - Anne Uhlmann
- Department of child and adolescent psychiatry, TU Dresden, Dresden, Saxony, Germany
| | - Aristotle Voineskos
- Center for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Temerty Faculty of Medicine, Toronto, ON, Canada
| | - Kun Yang
- Department of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Theo G M Van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA, USA
| | - Jessica A Turner
- Department of Psychiatry and Behavioral Health, Wexner Medical Center, The Ohio State University, Columbus, OH, USA
| | - Gianfranco Spalletta
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Federica Piras
- Neuropsychiatry Laboratory, Department of Clinical Neuroscience and Neurorehabilitation, IRCCS Santa Lucia Foundation, Rome, Italy
| |
Collapse
|
19
|
Yoo C, Kim MJ. Topographical similarity of cortical thickness represents generalized anxiety symptoms in adolescence. Brain Res Bull 2023; 202:110728. [PMID: 37558098 DOI: 10.1016/j.brainresbull.2023.110728] [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: 05/25/2023] [Revised: 08/04/2023] [Accepted: 08/05/2023] [Indexed: 08/11/2023]
Abstract
Generalized anxiety disorder (GAD) is a common condition characterized by excessive and uncontrollable worry, along with its high comorbidity rates. Despite increasing efforts to identify the neural underpinnings of GAD, neuroimaging research using cortical thickness have yielded largely inconsistent results. To address this, we adopted an inter-subject representational similarity analysis framework to explore a potential nonlinear relationship between vertex-wise cortical thickness and generalized anxiety symptom severity. We utilized a sample of 120 adolescents (13-18 years of age) from the Healthy Brain Network dataset. Here, we found greater topographical resemblance among participants with heightened generalized anxiety symptoms in the left caudal anterior cingulate and pericalcarine cortex. These results were not driven by the effects of age, sex, ADHD diagnosis, and GAD diagnosis. Such associations were not observed when including a group of younger participants (11-12 years of age) for analyses, highlighting the importance of age range selection when considering the link between cortical thickness and anxiety. Our findings reveal a novel cortical thickness topography that represents generalized anxiety in adolescents, which is embedded within the shared geometries between generalized anxiety symptoms and cortical thickness.
Collapse
Affiliation(s)
- Chaebin Yoo
- Department of Psychology, Sungkyunkwan University, Seoul 03063, South Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon 16419, South Korea
| | - M Justin Kim
- Department of Psychology, Sungkyunkwan University, Seoul 03063, South Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon 16419, South Korea.
| |
Collapse
|
20
|
Wronski ML, Geisler D, Bernardoni F, Seidel M, Bahnsen K, Doose A, Steinhäuser JL, Gronow F, Böldt LV, Plessow F, Lawson EA, King JA, Roessner V, Ehrlich S. Differential alterations of amygdala nuclei volumes in acutely ill patients with anorexia nervosa and their associations with leptin levels. Psychol Med 2023; 53:6288-6303. [PMID: 36464660 PMCID: PMC10358440 DOI: 10.1017/s0033291722003609] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/24/2022] [Accepted: 11/02/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND The amygdala is a subcortical limbic structure consisting of histologically and functionally distinct subregions. New automated structural magnetic resonance imaging (MRI) segmentation tools facilitate the in vivo study of individual amygdala nuclei in clinical populations such as patients with anorexia nervosa (AN) who show symptoms indicative of limbic dysregulation. This study is the first to investigate amygdala nuclei volumes in AN, their relationships with leptin, a key indicator of AN-related neuroendocrine alterations, and further clinical measures. METHODS T1-weighted MRI scans were subsegmented and multi-stage quality controlled using FreeSurfer. Left/right hemispheric amygdala nuclei volumes were cross-sectionally compared between females with AN (n = 168, 12-29 years) and age-matched healthy females (n = 168) applying general linear models. Associations with plasma leptin, body mass index (BMI), illness duration, and psychiatric symptoms were analyzed via robust linear regression. RESULTS Globally, most amygdala nuclei volumes in both hemispheres were reduced in AN v. healthy control participants. Importantly, four specific nuclei (accessory basal, cortical, medial nuclei, corticoamygdaloid transition in the rostral-medial amygdala) showed greater volumetric reduction even relative to reductions of whole amygdala and total subcortical gray matter volumes, whereas basal, lateral, and paralaminar nuclei were less reduced. All rostral-medially clustered nuclei were positively associated with leptin in AN independent of BMI. Amygdala nuclei volumes were not associated with illness duration or psychiatric symptom severity in AN. CONCLUSIONS In AN, amygdala nuclei are altered to different degrees. Severe volume loss in rostral-medially clustered nuclei, collectively involved in olfactory/food-related reward processing, may represent a structural correlate of AN-related symptoms. Hypoleptinemia might be linked to rostral-medial amygdala alterations.
Collapse
Affiliation(s)
- Marie-Louis Wronski
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
- Neuroendocrine Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Daniel Geisler
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Fabio Bernardoni
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Maria Seidel
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Klaas Bahnsen
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Arne Doose
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Jonas L. Steinhäuser
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Franziska Gronow
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
- Institute of Medical Psychology, Charité University Medicine Berlin, Berlin, Germany
| | - Luisa V. Böldt
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
- Charité University Medicine Berlin, Berlin, Germany
| | - Franziska Plessow
- Neuroendocrine Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Elizabeth A. Lawson
- Neuroendocrine Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Joseph A. King
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Veit Roessner
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
- Eating Disorder Treatment and Research Center, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany
| |
Collapse
|
21
|
Qi X, Xu W, Li G. Neuroimaging Study of Brain Functional Differences in Generalized Anxiety Disorder and Depressive Disorder. Brain Sci 2023; 13:1282. [PMID: 37759883 PMCID: PMC10526432 DOI: 10.3390/brainsci13091282] [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: 07/23/2023] [Revised: 08/23/2023] [Accepted: 08/31/2023] [Indexed: 09/29/2023] Open
Abstract
Generalized anxiety disorder (GAD) and depressive disorder (DD) are distinct mental disorders, which are characterized by complex and unique neuroelectrophysiological mechanisms in psychiatric neurosciences. The understanding of the brain functional differences between GAD and DD is crucial for the accurate diagnosis and clinical efficacy evaluation. The aim of this study was to reveal the differences in functional brain imaging between GAD and DD based on multidimensional electroencephalogram (EEG) characteristics. To this end, 10 min resting-state EEG signals were recorded from 38 GAD and 34 DD individuals. Multidimensional EEG features were subsequently extracted, which include power spectrum density (PSD), fuzzy entropy (FE), and phase lag index (PLI). Then, a direct statistical analysis (i.e., ANOVA) and three ensemble learning models (i.e., Random Forest (RF), Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost)) were used on these EEG features for the differential recognitions. Our results showed that DD has significantly higher PSD values in the alpha1 and beta band, and a higher FE in the beta band, in comparison with GAD, along with the aberrant functional connections in all four bands between GAD and DD. Moreover, machine learning analysis further revealed that the distinct features predominantly occurred in the beta band and functional connections. Here, we show that DD has higher power and more complex brain activity patterns in the beta band and reorganized brain functional network structures in all bands compared to GAD. In sum, these findings move towards the practical identification of brain functional differences between GAD and DD.
Collapse
Affiliation(s)
- Xuchen Qi
- Department of Neurosurgery, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China;
- Department of Neurosurgery, Shaoxing People’s Hospital, Shaoxing 312000, China
| | - Wanxiu Xu
- College of Engineering, Zhejiang Normal University, Jinhua 321004, China;
| | - Gang Li
- College of Mathematical Medicine, Zhejiang Normal University, Jinhua 321004, China
| |
Collapse
|
22
|
Zhu H, Li T, Zhao B. Statistical Learning Methods for Neuroimaging Data Analysis with Applications. Annu Rev Biomed Data Sci 2023; 6:73-104. [PMID: 37127052 DOI: 10.1146/annurev-biodatasci-020722-100353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The aim of this review is to provide a comprehensive survey of statistical challenges in neuroimaging data analysis, from neuroimaging techniques to large-scale neuroimaging studies and statistical learning methods. We briefly review eight popular neuroimaging techniques and their potential applications in neuroscience research and clinical translation. We delineate four themes of neuroimaging data and review major image processing analysis methods for processing neuroimaging data at the individual level. We briefly review four large-scale neuroimaging-related studies and a consortium on imaging genomics and discuss four themes of neuroimaging data analysis at the population level. We review nine major population-based statistical analysis methods and their associated statistical challenges and present recent progress in statistical methodology to address these challenges.
Collapse
Affiliation(s)
- Hongtu Zhu
- Department of Biostatistics, Department of Statistics, Department of Genetics, and Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina, USA;
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Tengfei Li
- Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, North Carolina, USA
- Department of Radiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| |
Collapse
|
23
|
Nasrullah N, Kerr WT, Stern JM, Wang Y, Tatekawa H, Lee JK, Karimi AH, Sreenivasan SS, Engel J, Eliashiv DE, Feusner JD, Salamon N, Savic I. Amygdala subfield and prefrontal cortex abnormalities in patients with functional seizures. Epilepsy Behav 2023; 145:109278. [PMID: 37356226 DOI: 10.1016/j.yebeh.2023.109278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 05/16/2023] [Accepted: 05/20/2023] [Indexed: 06/27/2023]
Abstract
BACKGROUND Functional seizures (FS) are paroxysmal episodes, resembling epileptic seizures, but without underlying epileptic abnormality. The aetiology and neuroanatomic associations are incompletely understood. Recent brain imaging data indicate cerebral changes, however, without clarifying possible pathophysiology. In the present study, we specifically investigated the neuroanatomic changes in subregions of the amygdala and hippocampus in FS. METHODS T1 MRI scans of 37 female patients with FS and 37 age-matched female seizure naïve controls (SNC) were analyzed retrospectively in FreeSurfer version 7.1. Seizure naïve controls included patients with depression and anxiety disorders. The analysis included whole-brain cortical thickness, subcortical volumes, and subfields of the amygdala and hippocampus. Group comparisons were carried out using multivariable linear models. RESULTS The FS and SNC groups did not differ in the whole hippocampus and amygdala volumes. However, patients had a significant reduction of the right lateral amygdala volume (p = 0.00041), an increase of the right central amygdala, (p = 0.037), and thinning of the left superior frontal gyrus (p = 0.024). Additional findings in patients were increased volumes of the right medial amygdala (p = 0.031), left anterior amygdala (p = 0.017), and left dentate gyrus of the hippocampus (p = 0.035). CONCLUSIONS The observations from the amygdala and hippocampus segmentation affirm that there are neuroanatomic associations of FS. The pattern of these changes aligned with some of the cerebral changes described in chronic stress conditions and depression. The pattern of detected changes further study, and may, after validation, provide biomarkers for diagnosis and treatment.
Collapse
Affiliation(s)
- Nilab Nasrullah
- Department of Women's and Children's Health, Karolinska Institute, Stockholm, Sweden; Neurology Clinic, Karolinska University Hospital, Stockholm, Sweden
| | - Wesley T Kerr
- Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA; Department of Neurology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA
| | - John M Stern
- Department of Neurology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA
| | - Yanlu Wang
- Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Hiroyuki Tatekawa
- Department of Radiology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA
| | - John K Lee
- Department of Neurology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA
| | - Amir H Karimi
- Department of Neurology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA
| | - Siddhika S Sreenivasan
- Department of Neurology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA
| | - Jerome Engel
- Department of Neurology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA; Brain Research Institute, University of California Los Angeles, Los Angeles, CA, USA; Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Dawn E Eliashiv
- Department of Neurology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA
| | - Jamie D Feusner
- Department of Women's and Children's Health, Karolinska Institute, Stockholm, Sweden; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA; Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Noriko Salamon
- Department of Radiology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA
| | - Ivanka Savic
- Department of Women's and Children's Health, Karolinska Institute, Stockholm, Sweden; Neurology Clinic, Karolinska University Hospital, Stockholm, Sweden; Department of Neurology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA.
| |
Collapse
|
24
|
Mendes SL, Pinaya WHL, Pan PM, Jackowski AP, Bressan RA, Sato JR. Generalizability of 3D CNN models for age estimation in diverse youth populations using structural MRI. Sci Rep 2023; 13:6886. [PMID: 37106035 PMCID: PMC10140022 DOI: 10.1038/s41598-023-33920-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 04/20/2023] [Indexed: 04/29/2023] Open
Abstract
Recently, several studies have investigated the neurodevelopment of psychiatric disorders using brain data acquired via structural magnetic resonance imaging (sMRI). These analyses have shown the potential of sMRI data to provide a relatively precise characterization of brain structural biomarkers. Despite these advances, a relatively unexplored question is how reliable and consistent a model is when assessing subjects from other independent datasets. In this study, we investigate the performance and generalizability of the same model architecture trained from distinct datasets comprising youths in diverse stages of neurodevelopment and with different mental health conditions. We employed models with the same 3D convolutional neural network (CNN) architecture to assess autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), brain age, and a measure of dimensional psychopathology, the Child Behavior Checklist (CBCL) total score. The investigated datasets include the Autism Brain Imaging Data Exchange II (ABIDE-II, N = 580), Attention Deficit Hyperactivity Disorder (ADHD-200, N = 922), Brazilian High-Risk Cohort Study (BHRCS, N = 737), and Adolescent Brain Cognitive Development (ABCD, N = 11,031). Models' performance and interpretability were assessed within each dataset (for diagnosis tasks) and inter-datasets (for age estimation). Despite the demographic and phenotypic differences of the subjects, all models presented significant estimations for age (p value < 0.001) within and between datasets. In addition, most models showed a moderate to high correlation in age estimation. The results, including the models' brain regions of interest (ROI), were analyzed and discussed in light of the youth neurodevelopmental structural changes. Among other interesting discoveries, we found that less confounded training datasets produce models with higher generalization capacity.
Collapse
Affiliation(s)
- Sergio Leonardo Mendes
- Center of Mathematics, Computing, and Cognition, Universidade Federal Do ABC, Rua Arcturus N. 03, São Bernardo Do Campo, SP, 09606-070, Brazil
| | | | - Pedro Mario Pan
- Escola Paulista de Medicina, Universidade Federal de São Paulo, R. Maj. Maragliano (UNIFESP), 241-Vila Mariana, São Paulo, SP, 04017-030, Brazil
| | - Andrea Parolin Jackowski
- Escola Paulista de Medicina, Universidade Federal de São Paulo, R. Maj. Maragliano (UNIFESP), 241-Vila Mariana, São Paulo, SP, 04017-030, Brazil
- Department of Education, ICT and Learning, Østfold University College, Halden, Norway
| | - Rodrigo Affonseca Bressan
- Escola Paulista de Medicina, Universidade Federal de São Paulo, R. Maj. Maragliano (UNIFESP), 241-Vila Mariana, São Paulo, SP, 04017-030, Brazil
| | - João Ricardo Sato
- Center of Mathematics, Computing, and Cognition, Universidade Federal Do ABC, Rua Arcturus N. 03, São Bernardo Do Campo, SP, 09606-070, Brazil
| |
Collapse
|
25
|
Nakua H, Hawco C, Forde NJ, Joseph M, Grillet M, Johnson D, Jacobs GR, Hill S, Voineskos A, Wheeler AL, Lai MC, Szatmari P, Georgiades S, Nicolson R, Schachar R, Crosbie J, Anagnostou E, Lerch JP, Arnold PD, Ameis SH. Systematic comparisons of different quality control approaches applied to three large pediatric neuroimaging datasets. Neuroimage 2023; 274:120119. [PMID: 37068719 DOI: 10.1016/j.neuroimage.2023.120119] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 03/22/2023] [Accepted: 04/14/2023] [Indexed: 04/19/2023] Open
Abstract
INTRODUCTION Poor quality T1-weighted brain scans systematically affect the calculation of brain measures. Removing the influence of such scans requires identifying and excluding scans with noise and artefacts through a quality control (QC) procedure. While QC is critical for brain imaging analyses, it is not yet clear whether different QC approaches lead to the exclusion of the same participants. Further, the removal of poor-quality scans may unintentionally introduce a sampling bias by excluding the subset of participants who are younger and/or feature greater clinical impairment. This study had two aims: 1) examine whether different QC approaches applied to T1-weighted scans would exclude the same participants, and 2) examine how exclusion of poor-quality scans impacts specific demographic, clinical and brain measure characteristics between excluded and included participants in three large pediatric neuroimaging samples. METHODS We used T1-weighted, resting-state fMRI, demographic and clinical data from the Province of Ontario Neurodevelopmental Disorders network (Aim 1: n=553, Aim 2: n=465), the Healthy Brain Network (Aim 1: n=1051, Aim 2: n=558), and the Philadelphia Neurodevelopmental Cohort (Aim 1: n=1087; Aim 2: n=619). Four different QC approaches were applied to T1-weighted MRI (visual QC, metric QC, automated QC, fMRI-derived QC). We used tetrachoric correlation and inter-rater reliability analyses to examine whether different QC approaches excluded the same participants. We examined differences in age, mental health symptoms, everyday/adaptive functioning, IQ and structural MRI-derived brain indices between participants that were included versus excluded following each QC approach. RESULTS Dataset-specific findings revealed mixed results with respect to overlap of QC exclusion. However, in POND and HBN, we found a moderate level of overlap between visual and automated QC approaches (rtet=0.52-0.59). Implementation of QC excluded younger participants, and tended to exclude those with lower IQ, and lower everyday/adaptive functioning scores across several approaches in a dataset-specific manner. Across nearly all datasets and QC approaches examined, excluded participants had lower estimates of cortical thickness and subcortical volume, but this effect did not differ by QC approach. CONCLUSION The results of this study provide insight into the influence of QC decisions on structural pediatric imaging analyses. While different QC approaches exclude different subsets of participants, the variation of influence of different QC approaches on clinical and brain metrics is minimal in large datasets. Overall, implementation of QC tends to exclude participants who are younger, and those who have more cognitive and functional impairment. Given that automated QC is standardized and can reduce between-study differences, the results of this study support the potential to use automated QC for large pediatric neuroimaging datasets.
Collapse
Affiliation(s)
- Hajer Nakua
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Colin Hawco
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Natalie J Forde
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Michael Joseph
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Maud Grillet
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Delaney Johnson
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Grace R Jacobs
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Sean Hill
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Aristotle Voineskos
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Anne L Wheeler
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada; Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Meng-Chuan Lai
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Peter Szatmari
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | - Rob Nicolson
- Department of Psychiatry, University of Western Ontario, London, Ontario, Canada
| | - Russell Schachar
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada; Genetics & Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Jennifer Crosbie
- Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada; Genetics & Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Evdokia Anagnostou
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario, Canada; Department of Pediatrics, University of Toronto, Toronto, Canada
| | - Jason P Lerch
- Mouse Imaging Centre, Hospital for Sick Children, Toronto, Ontario, Canada; Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, Canada; Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Paul D Arnold
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; Departments of Psychiatry and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Stephanie H Ameis
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada.
| |
Collapse
|
26
|
Groenewold NA, Bas-Hoogendam JM, Amod AR, Laansma MA, Van Velzen LS, Aghajani M, Hilbert K, Oh H, Salas R, Jackowski AP, Pan PM, Salum GA, Blair JR, Blair KS, Hirsch J, Pantazatos SP, Schneier FR, Talati A, Roelofs K, Volman I, Blanco-Hinojo L, Cardoner N, Pujol J, Beesdo-Baum K, Ching CRK, Thomopoulos SI, Jansen A, Kircher T, Krug A, Nenadić I, Stein F, Dannlowski U, Grotegerd D, Lemke H, Meinert S, Winter A, Erb M, Kreifelts B, Gong Q, Lui S, Zhu F, Mwangi B, Soares JC, Wu MJ, Bayram A, Canli M, Tükel R, Westenberg PM, Heeren A, Cremers HR, Hofmann D, Straube T, Doruyter AGG, Lochner C, Peterburs J, Van Tol MJ, Gur RE, Kaczkurkin AN, Larsen B, Satterthwaite TD, Filippi CA, Gold AL, Harrewijn A, Zugman A, Bülow R, Grabe HJ, Völzke H, Wittfeld K, Böhnlein J, Dohm K, Kugel H, Schrammen E, Zwanzger P, Leehr EJ, Sindermann L, Ball TM, Fonzo GA, Paulus MP, Simmons A, Stein MB, Klumpp H, Phan KL, Furmark T, Månsson KNT, Manzouri A, Avery SN, Blackford JU, Clauss JA, Feola B, Harper JC, Sylvester CM, Lueken U, Veltman DJ, Winkler AM, Jahanshad N, Pine DS, Thompson PM, Stein DJ, Van der Wee NJA. Volume of subcortical brain regions in social anxiety disorder: mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group. Mol Psychiatry 2023; 28:1079-1089. [PMID: 36653677 PMCID: PMC10804423 DOI: 10.1038/s41380-022-01933-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 10/31/2022] [Accepted: 12/15/2022] [Indexed: 01/20/2023]
Abstract
There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = -0.077, pFWE = 0.037; right: d = -0.104, pFWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = -0.034, pFWE = 0.045). Smaller bilateral putamen volumes (left: d = -0.141, pFWE < 0.001; right: d = -0.158, pFWE < 0.001) and larger bilateral pallidum volumes (left: d = 0.129, pFWE = 0.006; right: d = 0.099, pFWE = 0.046) were detected in adult SAD patients relative to controls, but no volumetric differences were apparent in adolescent SAD patients relative to controls. Comorbid anxiety disorders and age of SAD onset were additional determinants of SAD-related volumetric differences in subcortical regions. To conclude, subtle volumetric alterations in subcortical regions in SAD were detected. Heterogeneity in age and clinical characteristics may partly explain inconsistencies in previous findings. The association between alterations in subcortical volumes and SAD illness progression deserves further investigation, especially from adolescence into adulthood.
Collapse
Affiliation(s)
- Nynke A Groenewold
- Neuroscience Institute, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa.
- South African Medical Research Council (SA-MRC) Unit on Child and Adolescent Health, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa.
| | - Janna Marie Bas-Hoogendam
- Department of Psychiatry, Leiden University Medical Center, Leiden, Netherlands
- Department of Developmental and Educational Psychology, Institute of Psychology, Leiden University, Leiden, Netherlands
- Leiden Institute for Brain and Cognition, Leiden, Netherlands
| | - Alyssa R Amod
- Neuroscience Institute, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Max A Laansma
- Department of Anatomy & Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Laura S Van Velzen
- Orygen & Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Moji Aghajani
- Leiden University, Institute of Education & Child Studies, Section Forensic Family & Youth Care, Leiden, Netherlands
| | - Kevin Hilbert
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Hyuntaek Oh
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Ramiro Salas
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
- Michael E DeBakey VA Medical Center, Center for Translational Research on Inflammatory Diseases, Houston, TX, USA
| | - Andrea P Jackowski
- LiNC, Department of Psychiatry, Federal University of São Paulo, São Paulo, SP, Brazil
| | - Pedro M Pan
- LiNC, Department of Psychiatry, Federal University of São Paulo, São Paulo, SP, Brazil
| | - Giovanni A Salum
- Section on Negative Affect and Social Processes, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - James R Blair
- Child and Adolescent Mental Health Centre, Mental Health Services, Capital Region of Denmark, Copenhagen, Denmark
| | - Karina S Blair
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Joy Hirsch
- Departments of Psychiatry & Neurobiology, Yale School of Medicine, New Haven, CT, USA
| | - Spiro P Pantazatos
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Franklin R Schneier
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Ardesheer Talati
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Karin Roelofs
- Donders Institute for Brain, Cognition and Behavior, Radboud University Behavioral Science Institute, Radboud University, Nijmegen, Netherlands
| | - Inge Volman
- Wellcome Centre for Integrative Neuroimaging Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford, UK
| | - Laura Blanco-Hinojo
- MRI Research Unit, Department of Radiology, Hospital del Mar, Barcelona, Spain
- Centro Investigación Biomédica en Red de Salud Mental, CIBERSAM G21, Barcelona, Spain
| | - Narcís Cardoner
- Department of Mental Health, University Hospital Parc Taulí-I3PT, Barcelona, Spain, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Carlos III Health Institute, Madrid, Spain
| | - Jesus Pujol
- MRI Research Unit, Department of Radiology, Hospital del Mar, Barcelona, Spain
- Centro Investigación Biomédica en Red de Salud Mental, CIBERSAM G21, Barcelona, Spain
| | - Katja Beesdo-Baum
- Behavioral Epidemiology, Institute of Clinical Psycholog and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Christopher R K Ching
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Andreas Jansen
- Core-Facility Brainimaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Axel Krug
- Department of Psychiatry, University of Marburg, Marburg, Germany
- Department of Psychiatry, University Hospital of Bonn, Bonn, Germany
| | - Igor Nenadić
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hannah Lemke
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Michael Erb
- Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Benjamin Kreifelts
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), University of Tübingen, Tübingen, Germany
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Fei Zhu
- Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Benson Mwangi
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jair C Soares
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Mon-Ju Wu
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ali Bayram
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, Istanbul, Turkey
| | - Mesut Canli
- Department of Physiology, Istanbul University, Istanbul, Turkey
| | - Raşit Tükel
- Department of Psychiatry, Istanbul University, Istanbul, Turkey
| | - P Michiel Westenberg
- Department of Developmental and Educational Psychology, Institute of Psychology, Leiden University, Leiden, Netherlands
- Leiden Institute for Brain and Cognition, Leiden, Netherlands
| | - Alexandre Heeren
- Psychological Science Research Institute, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Henk R Cremers
- Department of Clinical Psychology, University of Amsterdam, Amsterdam, Netherlands
| | - David Hofmann
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
| | - Thomas Straube
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
| | | | - Christine Lochner
- SA-MRC Unit on Risk and Resilience in Mental Disorders, Stellenbosch University, Stellenbosch, South Africa
| | - Jutta Peterburs
- Institute of Systems Medicine and Faculty of Human Medicine, MSH Medical School Hamburg, Hamburg, Germany
| | - Marie-José Van Tol
- Cognitive Neuroscience Center, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Bart Larsen
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Courtney A Filippi
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Andrea L Gold
- Department of Psychiatry and Human Behavior, Brown University Warren Alpert Medical School, Providence, RI, USA
| | - Anita Harrewijn
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, Netherlands
| | - André Zugman
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Robin Bülow
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Joscha Böhnlein
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Harald Kugel
- University Clinic for Radiology, University of Münster, Münster, Germany
| | - Elisabeth Schrammen
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Peter Zwanzger
- KBO-Inn-Salzach-Klinikum, Munich, Germany
- Department of Psychiatry and Psychotherapy, Ludwig Maximilians University of Munich, Munich, Germany
| | - Elisabeth J Leehr
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Lisa Sindermann
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Tali M Ball
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Gregory A Fonzo
- Department of Psychiatry and Behavioral Sciences, The University of Texas at Austin Dell Medical School, Austin, TX, USA
| | | | - Alan Simmons
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Murray B Stein
- Departments of Psychiatry & School of Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Heide Klumpp
- Departments of Psychology & Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - K Luan Phan
- Department of Psychiatry & Behavioral Health, the Ohio State University, Columbus, OH, USA
| | - Tomas Furmark
- Department of Psychology, Uppsala University, Uppsala, Sweden
| | | | | | - Suzanne N Avery
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | - Brandee Feola
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Chad M Sylvester
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Ulrike Lueken
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC location VUMC, Amsterdam, Netherlands
| | - Anderson M Winkler
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Daniel S Pine
- Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Dan J Stein
- Neuroscience Institute, Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- SA-MRC Unit on Risk & Resilience in Mental Disorders, University of Cape Town, Cape Town, South Africa
| | - Nic J A Van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, Netherlands
- Leiden Institute for Brain and Cognition, Leiden, Netherlands
| |
Collapse
|
27
|
History of suicide attempt associated with amygdala and hippocampus changes among individuals with schizophrenia. Eur Arch Psychiatry Clin Neurosci 2023:10.1007/s00406-023-01554-5. [PMID: 36788147 DOI: 10.1007/s00406-023-01554-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 01/09/2023] [Indexed: 02/16/2023]
Abstract
Abnormalities in subcortical brain structures may reflect higher suicide risk in mood disorders, but less is known about its associations for schizophrenia. This cross-sectional imaging study aimed to explore whether the history of suicide attempts was associated with subcortical changes among individuals with schizophrenia. We recruited 44 individuals with schizophrenia and a history of suicide attempts (SZ-SA) and 44 individuals with schizophrenia but without a history of suicide attempts (SZ-NSA) and 44 healthy controls. Linear regression showed that SZ-SA had smaller volumes of the hippocampus (Cohen's d = -0.72), the amygdala (Cohen's d = -0.69), and some nuclei of the amygdala (Cohen's d, -0.57 to -0.72) than SZ-NSA after adjusting for age, sex, illness phase, and intracranial volume. There was no difference in the volume of the subfields of the hippocampus. It suggests the history of suicide attempts is associated with subcortical volume alterations in schizophrenia.
Collapse
|
28
|
Khosravi P, Zugman A, Amelio P, Winkler AM, Pine DS. Translating Big Data to Clinical Outcomes in Anxiety: Potential for Multimodal Integration. Curr Psychiatry Rep 2022; 24:841-851. [PMID: 36469202 PMCID: PMC9931491 DOI: 10.1007/s11920-022-01385-6] [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] [Accepted: 10/16/2022] [Indexed: 12/12/2022]
Abstract
PURPOSE OF THE REVIEW This review describes approaches to research on anxiety that attempt to link neural correlates to treatment response and novel therapies. The review emphasizes pediatric anxiety disorders since most anxiety disorders begin before adulthood. RECENT FINDINGS Recent literature illustrates how current treatments for anxiety manifest diverse relations with a range of neural markers. While some studies demonstrate post-treatment normalization of markers in anxious individuals, others find persistence of group differences. For other markers, which show no pretreatment association with anxiety, the markers nevertheless distinguish treatment-responders from non-responders. Heightened error related negativity represents the risk marker discussed in the most depth; however, limitations in measures related to error responding necessitate multimodal and big-data approaches. Single risk markers show limits as correlates of treatment response. Large-scale, multimodal data analyzed with predictive models may illuminate additional risk markers related to anxiety disorder treatment outcomes. Such work may identify novel targets and eventually guide improvements in treatment response/outcomes.
Collapse
Affiliation(s)
- Parmis Khosravi
- Section on Development and Affective Neuroscience, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, MD, Bethesda, USA.
| | - André Zugman
- Section on Development and Affective Neuroscience, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, MD, Bethesda, USA
| | - Paia Amelio
- Section on Development and Affective Neuroscience, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, MD, Bethesda, USA
| | - Anderson M Winkler
- Section on Development and Affective Neuroscience, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, MD, Bethesda, USA
| | - Daniel S Pine
- Section on Development and Affective Neuroscience, Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, MD, Bethesda, USA
| |
Collapse
|
29
|
Sun D, Rakesh G, Haswell CC, Logue M, Baird CL, O'Leary EN, Cotton AS, Xie H, Tamburrino M, Chen T, Dennis EL, Jahanshad N, Salminen LE, Thomopoulos SI, Rashid F, Ching CRK, Koch SBJ, Frijling JL, Nawijn L, van Zuiden M, Zhu X, Suarez-Jimenez B, Sierk A, Walter H, Manthey A, Stevens JS, Fani N, van Rooij SJH, Stein M, Bomyea J, Koerte IK, Choi K, van der Werff SJA, Vermeiren RRJM, Herzog J, Lebois LAM, Baker JT, Olson EA, Straube T, Korgaonkar MS, Andrew E, Zhu Y, Li G, Ipser J, Hudson AR, Peverill M, Sambrook K, Gordon E, Baugh L, Forster G, Simons RM, Simons JS, Magnotta V, Maron-Katz A, du Plessis S, Disner SG, Davenport N, Grupe DW, Nitschke JB, deRoon-Cassini TA, Fitzgerald JM, Krystal JH, Levy I, Olff M, Veltman DJ, Wang L, Neria Y, De Bellis MD, Jovanovic T, Daniels JK, Shenton M, van de Wee NJA, Schmahl C, Kaufman ML, Rosso IM, Sponheim SR, Hofmann DB, Bryant RA, Fercho KA, Stein DJ, Mueller SC, Hosseini B, Phan KL, McLaughlin KA, Davidson RJ, Larson CL, May G, Nelson SM, Abdallah CG, Gomaa H, Etkin A, Seedat S, Harpaz-Rotem I, Liberzon I, van Erp TGM, Quidé Y, Wang X, Thompson PM, Morey RA. A comparison of methods to harmonize cortical thickness measurements across scanners and sites. Neuroimage 2022; 261:119509. [PMID: 35917919 PMCID: PMC9648725 DOI: 10.1016/j.neuroimage.2022.119509] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 07/07/2022] [Accepted: 07/22/2022] [Indexed: 12/02/2022] Open
Abstract
Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants' demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3-85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects.
Collapse
Affiliation(s)
- Delin Sun
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.; Department of Veteran Affairs (VA) Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA.; Department of Psychology, The Education University of Hong Kong, Hong Kong, China
| | - Gopalkumar Rakesh
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.; Department of Veteran Affairs (VA) Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA
| | - Courtney C Haswell
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.; Department of Veteran Affairs (VA) Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA
| | - Mark Logue
- National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA.; Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA.; Biomedical Genetics, Boston University School of Medicine, Boston, MA, USA.; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - C Lexi Baird
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.; Department of Veteran Affairs (VA) Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA
| | - Erin N O'Leary
- Department of Psychiatry, University of Toledo, Toledo, OH, USA
| | - Andrew S Cotton
- Department of Psychiatry, University of Toledo, Toledo, OH, USA
| | - Hong Xie
- Department of Psychiatry, University of Toledo, Toledo, OH, USA
| | | | - Tian Chen
- Department of Psychiatry, University of Toledo, Toledo, OH, USA.; Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Boston, MA, USA
| | - Emily L Dennis
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Boston, MA, USA.; Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA.; Department of Neurology, University of Utah, Salt Lake City, UT, USA.; Stanford Neurodevelopment, Affect, and Psychopathology Laboratory, Stanford, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Lauren E Salminen
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Faisal Rashid
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Christopher R K Ching
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Saskia B J Koch
- Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.; Donders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Jessie L Frijling
- Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Laura Nawijn
- Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.; Department of Psychiatry, Amsterdam University Medical Centers, VU University Medical Center, VU University, Amsterdam, The Netherlands
| | - Mirjam van Zuiden
- Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Xi Zhu
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA.; New York State Psychiatric Institute, New York, NY, USA
| | - Benjamin Suarez-Jimenez
- Del Monte Institute for Neuroscience, University of Rochester Medical Center, Rochester, NY, USA.; Department of Psychiatry, Columbia University Medical Center, New York, NY, USA.; New York State Psychiatric Institute, New York, NY, USA
| | - Anika Sierk
- University Medical Centre Charité, Berlin, Germany
| | | | | | - Jennifer S Stevens
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Negar Fani
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Sanne J H van Rooij
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Murray Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Jessica Bomyea
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Inga K Koerte
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Boston, MA, USA.; Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, Ludwig-Maximilians-Universität, Munich, Germany
| | - Kyle Choi
- Health Services Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Steven J A van der Werff
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands.; Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | | | - Julia Herzog
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Lauren A M Lebois
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.; Division of Depression and Anxiety Disorders, McLean Hospital, Belmont, MA, USA
| | - Justin T Baker
- Institute for Technology in Psychiatry, McLean Hospital, Harvard University, Belmont, MA, USA
| | - Elizabeth A Olson
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.; Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Thomas Straube
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
| | - Mayuresh S Korgaonkar
- Brain Dynamics Centre, Westmead Institute of Medical Research, University of Sydney, Westmead, NSW, Australia
| | - Elpiniki Andrew
- Department of Psychology, University of Sydney, Westmead, NSW, Australia
| | - Ye Zhu
- Laboratory for Traumatic Stress Studies, Chinese Academy of Sciences Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Gen Li
- Laboratory for Traumatic Stress Studies, Chinese Academy of Sciences Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Jonathan Ipser
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Anna R Hudson
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Matthew Peverill
- Department of Psychology, University of Washington, Seattle, WA, USA
| | - Kelly Sambrook
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Evan Gordon
- Department of Radiology, Washington University, St. Louis, MO, USA
| | - Lee Baugh
- Division of Basic Biomedical Sciences, Sanford School of Medicine, University of South Dakota, Vermillion, SD, USA.; Center for Brain and Behavior Research, University of South Dakota, Vermillion, SD, USA.; Sioux Falls VA Health Care System, Sioux Falls, SD, USA
| | - Gina Forster
- Division of Basic Biomedical Sciences, Sanford School of Medicine, University of South Dakota, Vermillion, SD, USA.; Center for Brain and Behavior Research, University of South Dakota, Vermillion, SD, USA.; Brain Health Research Centre, Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - Raluca M Simons
- Center for Brain and Behavior Research, University of South Dakota, Vermillion, SD, USA.; Department of Psychology, University of South Dakota, Vermillion, SD, USA
| | - Jeffrey S Simons
- Sioux Falls VA Health Care System, Sioux Falls, SD, USA.; Department of Psychology, University of South Dakota, Vermillion, SD, USA
| | - Vincent Magnotta
- Department of Radiology, Psychiatry, and Biomedical Engineering, University of Iowa, Iowa City, IA, USA
| | - Adi Maron-Katz
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Stefan du Plessis
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Seth G Disner
- Minneapolis VA Health Care System, Minneapolis, MN, USA.; Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Nicholas Davenport
- Minneapolis VA Health Care System, Minneapolis, MN, USA.; Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Daniel W Grupe
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA
| | - Jack B Nitschke
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Terri A deRoon-Cassini
- Department of Surgery, Division of Trauma and Acute Care Surgery, Medical College of Wisconsin, Milwaukee, WI, USA
| | | | - John H Krystal
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA.; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Ifat Levy
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA.; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Miranda Olff
- Department of Psychiatry, Amsterdam University Medical Centers, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.; ARQ National Psychotrauma Centre, Diemen, The Netherlands
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam University Medical Center, location VUMC, Amsterdam, The Netherlands
| | - Li Wang
- Laboratory for Traumatic Stress Studies, Chinese Academy of Sciences Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Yuval Neria
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA.; New York State Psychiatric Institute, New York, NY, USA
| | - Michael D De Bellis
- Healthy Childhood Brain Development Developmental Traumatology Research Program, Department of Psychiatry and Behavioral Sciences, Duke University, Durham, NC, USA
| | - Tanja Jovanovic
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, USA
| | - Judith K Daniels
- Department of Clinical Psychology, University of Groningen, Groningen, The Netherlands
| | - Martha Shenton
- Psychiatry Neuroimaging Laboratory, Brigham & Women's Hospital, Boston, MA, USA.; VA Boston Healthcare System, Brockton Division, Brockton, MA, USA
| | - Nic J A van de Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands.; Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Christian Schmahl
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Milissa L Kaufman
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.; Division of Women's Mental Health, McLean Hospital, Belmont, MA, USA
| | - Isabelle M Rosso
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.; Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Scott R Sponheim
- Minneapolis VA Health Care System, Minneapolis, MN, USA.; Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - David Bernd Hofmann
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
| | - Richard A Bryant
- School of Psychology, University of New South Wales, Sydney, NSW, Australia
| | - Kelene A Fercho
- Division of Basic Biomedical Sciences, Sanford School of Medicine, University of South Dakota, Vermillion, SD, USA.; Center for Brain and Behavior Research, University of South Dakota, Vermillion, SD, USA.; Sioux Falls VA Health Care System, Sioux Falls, SD, USA.; Civil Aerospace Medical Institute, US Federal Aviation Administration, Oklahoma City, OK, USA
| | - Dan J Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Sven C Mueller
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Bobak Hosseini
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - K Luan Phan
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA.; Mental Health Service Line, Jesse Brown VA Chicago Health Care System, Chicago, IL, USA
| | | | - Richard J Davidson
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, USA.; Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA.; Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - Christine L Larson
- Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, USA
| | - Geoffrey May
- Veterans Integrated Service Network-17 Center of Excellence for Research on Returning War Veterans, Waco, TX, USA.; Department of Psychology and Neuroscience, Baylor University, Waco, TX, USA.; Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA.; Department of Psychiatry and Behavioral Science, Texas A&M University Health Science Center, Bryan, TX, USA
| | - Steven M Nelson
- Veterans Integrated Service Network-17 Center of Excellence for Research on Returning War Veterans, Waco, TX, USA.; Department of Psychology and Neuroscience, Baylor University, Waco, TX, USA.; Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA.; Department of Psychiatry and Behavioral Science, Texas A&M University Health Science Center, Bryan, TX, USA
| | - Chadi G Abdallah
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA.; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Hassaan Gomaa
- Department of Psychiatry and Behavioral Health, Pennsylvania State University, Hershey, PA, USA
| | - Amit Etkin
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.; VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Soraya Seedat
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Ilan Harpaz-Rotem
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA.; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Israel Liberzon
- Department of Psychiatry and Behavioral Science, Texas A&M University, College Station, TX, USA
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA.; Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, USA
| | - Yann Quidé
- School of Psychology, The University of New South Wales, Sydney, NSW, Australia.; Neuroscience Research Australia, Randwick, NSW, Australia
| | - Xin Wang
- Department of Mathematics and Statistics, University of Toledo, Toledo, OH, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Rajendra A Morey
- Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.; Department of Veteran Affairs (VA) Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham, NC, USA..
| |
Collapse
|
30
|
Fouche JP, Groenewold NA, Sevenoaks T, Heany S, Lochner C, Alonso P, Batistuzzo MC, Cardoner N, Ching CRK, de Wit SJ, Gutman B, Hoexter MQ, Jahanshad N, Kim M, Kwon JS, Mataix-Cols D, Menchon JM, Miguel EC, Nakamae T, Phillips ML, Pujol J, Sakai Y, Yun JY, Soriano-Mas C, Thompson PM, Yamada K, Veltman DJ, van den Heuvel OA, Stein DJ. Shape analysis of subcortical structures in obsessive-compulsive disorder and the relationship with comorbid anxiety, depression, and medication use: A meta-analysis by the OCD Brain Imaging Consortium. Brain Behav 2022; 12:e2755. [PMID: 36106505 PMCID: PMC9575597 DOI: 10.1002/brb3.2755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 08/09/2022] [Accepted: 08/16/2022] [Indexed: 11/29/2022] Open
Abstract
OBJECTIVE Neuroimaging studies of obsessive-compulsive disorder (OCD) patients have highlighted the important role of deep gray matter structures. Less work has however focused on subcortical shape in OCD patients. METHODS Here we pooled brain MRI scans from 412 OCD patients and 368 controls to perform a meta-analysis utilizing the ENIGMA-Shape protocol. In addition, we investigated modulating effects of medication status, comorbid anxiety or depression, and disease duration on subcortical shape. RESULTS There was no significant difference in shape thickness or surface area between OCD patients and healthy controls. For the subgroup analyses, OCD patients with comorbid depression or anxiety had lower thickness of the hippocampus and caudate nucleus and higher thickness of the putamen and pallidum compared to controls. OCD patients with comorbid depression had lower shape surface area in the thalamus, caudate nucleus, putamen, hippocampus, and nucleus accumbens and higher shape surface area in the pallidum. OCD patients with comorbid anxiety had lower shape surface area in the putamen and the left caudate nucleus and higher shape surface area in the pallidum and the right caudate nucleus. Further, OCD patients on medication had lower shape thickness of the putamen, thalamus, and hippocampus and higher thickness of the pallidum and caudate nucleus, as well as lower shape surface area in the hippocampus and amygdala and higher surface area in the putamen, pallidum, and caudate nucleus compared to controls. There were no significant differences between OCD patients without co-morbid anxiety and/or depression and healthy controls on shape measures. In addition, there were also no significant differences between OCD patients not using medication and healthy controls. CONCLUSIONS The findings here are partly consistent with prior work on brain volumes in OCD, insofar as they emphasize that alterations in subcortical brain morphology are associated with comorbidity and medication status. Further work is needed to understand the biological processes contributing to subcortical shape.
Collapse
Affiliation(s)
- Jean-Paul Fouche
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Nynke A Groenewold
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Tatum Sevenoaks
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Sarah Heany
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Christine Lochner
- SAMRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, Stellenbosch, South Africa
| | - Pino Alonso
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute, IDIBELL, Barcelona, Spain.,Carlos III Health Institute, Centro de Investigacion Biomedica en Red de Salud Mental (CIBERSAM), Madrid, Spain.,Department of Clinical Sciences, School of Medicine, University of Barcelona, Barcelona, Spain
| | - Marcelo C Batistuzzo
- Department & Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil.,Department of Methods and Techniques in Psychology, Pontifical Catholic University, Sao Paulo, SP, Brazil
| | - Narcis Cardoner
- Carlos III Health Institute, Centro de Investigacion Biomedica en Red de Salud Mental (CIBERSAM), Madrid, Spain.,Sant Pau Mental Health Group, Institut d'Investigacio Biomedica Sant Pau (IBB-Sant Pau), Hospital de la Sant Creu i Sant Pau, Barcelona, Spain.,Department of Psychiatry and Forensic Medicine, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Christopher R K Ching
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Stella J de Wit
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam Neuroscience, Amsterdam, The Netherlands.,Department of Anatomy & Neurosciences, Amsterdam UMC, Vrije Universiteit, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Boris Gutman
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, USA
| | - Marcelo Q Hoexter
- Department & Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Neda Jahanshad
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Minah Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jun Soo Kwon
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.,Institute of Human Behavioral Medicine, SNU MRC, Seoul, Republic of Korea.,Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
| | - David Mataix-Cols
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Jose M Menchon
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute, IDIBELL, Barcelona, Spain.,Carlos III Health Institute, Centro de Investigacion Biomedica en Red de Salud Mental (CIBERSAM), Madrid, Spain.,Department of Clinical Sciences, School of Medicine, University of Barcelona, Barcelona, Spain
| | - Euripedes C Miguel
- Department & Institute of Psychiatry, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | - Takashi Nakamae
- Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, USA
| | - Jesus Pujol
- MRI Research Unit, Radiology Department, Hospital del Mar, Barcelona, Spain
| | - Yuki Sakai
- Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan.,ATR Brain Information Communication Research Laboratory Group, Kyoto, Japan
| | - Je-Yeon Yun
- Seoul National University Hospital, Seoul, Republic of Korea.,Yeongeon Student Support Center, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Carles Soriano-Mas
- Department of Psychiatry, Bellvitge University Hospital, Bellvitge Biomedical Research Institute, IDIBELL, Barcelona, Spain.,Carlos III Health Institute, Centro de Investigacion Biomedica en Red de Salud Mental (CIBERSAM), Madrid, Spain.,Department of Social Psychology and Quantitative Psychology, Universitat de Barcelona-UB, Barcelona, Spain
| | - Paul M Thompson
- Imaging Genetics Center, USC Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Marina del Rey, California, USA
| | - Kei Yamada
- Department of Radiology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam Neuroscience, Amsterdam, The Netherlands.,Department of Anatomy & Neurosciences, Amsterdam UMC, Vrije Universiteit, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Odile A van den Heuvel
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit, Amsterdam Neuroscience, Amsterdam, The Netherlands.,Department of Anatomy & Neurosciences, Amsterdam UMC, Vrije Universiteit, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Dan J Stein
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa.,SAMRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, Stellenbosch, South Africa
| |
Collapse
|
31
|
Liu X, Klugah-Brown B, Zhang R, Chen H, Zhang J, Becker B. Pathological fear, anxiety and negative affect exhibit distinct neurostructural signatures: evidence from psychiatric neuroimaging meta-analysis. Transl Psychiatry 2022; 12:405. [PMID: 36151073 PMCID: PMC9508096 DOI: 10.1038/s41398-022-02157-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 09/04/2022] [Accepted: 09/06/2022] [Indexed: 11/24/2022] Open
Abstract
Internalizing disorders encompass anxiety, fear and depressive disorders, which exhibit overlap at both conceptual and symptom levels. Given that a neurobiological evaluation is lacking, we conducted a Seed-based D-Mapping comparative meta-analysis including coordinates as well as original statistical maps to determine common and disorder-specific gray matter volume alterations in generalized anxiety disorder (GAD), fear-related anxiety disorders (FAD, i.e., social anxiety disorder, specific phobias, panic disorder) and major depressive disorder (MDD). Results showed that GAD exhibited disorder-specific altered volumes relative to FAD including decreased volumes in left insula and lateral/medial prefrontal cortex as well as increased right putamen volume. Both GAD and MDD showed decreased prefrontal volumes compared to controls and FAD. While FAD showed less robust alterations in lingual gyrus compared to controls, this group presented intact frontal integrity. No shared structural abnormalities were found. Our study is the first to provide meta-analytic evidence for distinct neuroanatomical abnormalities underlying the pathophysiology of anxiety-, fear-related and depressive disorders. These findings may have implications for determining promising target regions for disorder-specific neuromodulation interventions (e.g. transcranial magnetic stimulation or neurofeedback).
Collapse
Affiliation(s)
- Xiqin Liu
- grid.54549.390000 0004 0369 4060The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731 Chengdu, P. R. China
| | - Benjamin Klugah-Brown
- grid.54549.390000 0004 0369 4060The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731 Chengdu, P. R. China
| | - Ran Zhang
- grid.54549.390000 0004 0369 4060The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731 Chengdu, P. R. China
| | - Huafu Chen
- grid.54549.390000 0004 0369 4060The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People’s Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731 Chengdu, P. R. China
| | - Jie Zhang
- grid.8547.e0000 0001 0125 2443Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, 200433 Shanghai, P. R. China ,grid.8547.e0000 0001 0125 2443Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Fudan University, Ministry of Education, 200433 Shanghai, P. R. China
| | - Benjamin Becker
- The Center of Psychosomatic Medicine, Sichuan Provincial Center for Mental Health, Sichuan Provincial People's Hospital, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, 611731, Chengdu, P. R. China.
| |
Collapse
|
32
|
Kerr WT, Tatekawa H, Lee JK, Karimi AH, Sreenivasan SS, O'Neill J, Smith JM, Hickman LB, Savic I, Nasrullah N, Espinoza R, Narr K, Salamon N, Beimer NJ, Hadjiiski LM, Eliashiv DS, Stacey WC, Engel J, Feusner JD, Stern JM. Clinical MRI morphological analysis of functional seizures compared to seizure-naïve and psychiatric controls. Epilepsy Behav 2022; 134:108858. [PMID: 35933959 DOI: 10.1016/j.yebeh.2022.108858] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 06/26/2022] [Accepted: 07/15/2022] [Indexed: 11/15/2022]
Abstract
PURPOSE Functional seizures (FS), also known as psychogenic nonepileptic seizures (PNES), are physical manifestations of acute or chronic psychological distress. Functional and structural neuroimaging have identified objective signs of this disorder. We evaluated whether magnetic resonance imaging (MRI) morphometry differed between patients with FS and clinically relevant comparison populations. METHODS Quality-screened clinical-grade MRIs were acquired from 666 patients from 2006 to 2020. Morphometric features were quantified with FreeSurfer v6. Mixed-effects linear regression compared the volume, thickness, and surface area within 201 regions-of-interest for 90 patients with FS, compared to seizure-naïve patients with depression (n = 243), anxiety (n = 68), and obsessive-compulsive disorder (OCD, n = 41), respectively, and to other seizure-naïve controls with similar quality MRIs, accounting for the influence of multiple confounds including depression and anxiety based on chart review. These comparison populations were obtained through review of clinical records plus research studies obtained on similar scanners. RESULTS After Bonferroni-Holm correction, patients with FS compared with seizure-naïve controls exhibited thinner bilateral superior temporal cortex (left 0.053 mm, p = 0.014; right 0.071 mm, p = 0.00006), thicker left lateral occipital cortex (0.052 mm, p = 0.0035), and greater left cerebellar white-matter volume (1085 mm3, p = 0.0065). These findings were not accounted for by lower MRI quality in patients with FS. CONCLUSIONS These results reinforce prior indications of structural neuroimaging correlates of FS and, in particular, distinguish brain morphology in FS from that in depression, anxiety, and OCD. Future work may entail comparisons with other psychiatric disorders including bipolar and schizophrenia, as well as exploration of brain structural heterogeneity within FS.
Collapse
Affiliation(s)
- Wesley T Kerr
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA.
| | - Hiroyuki Tatekawa
- Department of Radiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - John K Lee
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Amir H Karimi
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Siddhika S Sreenivasan
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Joseph O'Neill
- Division of Child & Adolescent Psychiatry, Jane & Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA; Brain Research Institute, University of California Los Angeles, Los Angeles, CA, USA
| | - Jena M Smith
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - L Brian Hickman
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Ivanka Savic
- Department of Women's and Children's Health, Karolinska Institute and Neurology Clinic, Karolinksa University Hospital, Karolinska Universitetssjukhuset, Stockholm, Sweden
| | - Nilab Nasrullah
- Department of Women's and Children's Health, Karolinska Institute and Neurology Clinic, Karolinksa University Hospital, Karolinska Universitetssjukhuset, Stockholm, Sweden
| | - Randall Espinoza
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Katherine Narr
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Noriko Salamon
- Department of Radiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Nicholas J Beimer
- Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA; Department of Psychiatry, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Lubomir M Hadjiiski
- Department of Radiology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Dawn S Eliashiv
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - William C Stacey
- Department of Neurology, Michigan Medicine, University of Michigan, Ann Arbor, MI, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Jerome Engel
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA; Brain Research Institute, University of California Los Angeles, Los Angeles, CA, USA; Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Jamie D Feusner
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA; Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada; Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - John M Stern
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| |
Collapse
|
33
|
Abnormalities in the default mode network in late-life depression: A study of resting-state fMRI. Int J Clin Health Psychol 2022; 22:100317. [PMID: 35662792 PMCID: PMC9156943 DOI: 10.1016/j.ijchp.2022.100317] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 05/10/2022] [Indexed: 11/23/2022] Open
Abstract
Background/Objective Neuroimaging studies have reported abnormalities in the examination of functional connectivity in late-life depression (LLD) in the default mode network (DMN). The present study aims to study resting-state functional connectivity within the DMN in people diagnosed with late-life major depressive disorder (MDD) compared to healthy controls (HCs). Moreover, we would like to differentiate these same connectivity patterns between participants with high vs. low anxiety levels. Method The sample comprised 56 participants between the ages of 60 and 75; 27 of them were patients with a diagnosis of MDD. Patients were further divided into two samples according to anxiety level: the four people with the highest anxiety level and the five with the lowest anxiety level. Clinical aspects were measured using psychological questionnaires. Each participant underwent functional magnetic resonance imaging (fMRI) acquisition in different regions of interest (ROIs) of the DMN. Results There was a greater correlation between pairs of ROIs in the control group than in patients with LLD, being this effect preferentially observed in patients with higher anxiety levels. Conclusions There are differences in functional connectivity within the DMN depending on the level of psychopathology. This can be reflected in these correlations and in the number of clusters and how the brain lateralizes (clustering).
Collapse
|
34
|
Bas-Hoogendam JM, Bernstein R, Benson BE, Buss KA, Gunther KE, Pérez-Edgar K, Salum GA, Jackowski AP, Bressan RA, Zugman A, Degnan KA, Filippi CA, Fox NA, Henderson HA, Tang A, Zeytinoglu S, Harrewijn A, Hillegers MHJ, White T, van IJzendoorn MH, Schwartz CE, Felicione JM, DeYoung KA, Shackman AJ, Smith JF, Tillman RM, van den Berg YHM, Cillessen AHN, Roelofs K, Tyborowska A, Hill SY, Battaglia M, Tettamanti M, Dougherty LR, Jin J, Klein DN, Leung HC, Avery SN, Blackford JU, Clauss JA, Hayden EP, Liu P, Vandermeer MRJ, Goldsmith HH, Planalp EM, Nichols TE, Thompson PM, Westenberg PM, van der Wee NJA, Groenewold NA, Stein DJ, Winkler AM, Pine DS. Structural Brain Correlates of Childhood Inhibited Temperament: An ENIGMA-Anxiety Mega-analysis. J Am Acad Child Adolesc Psychiatry 2022; 61:1182-1188. [PMID: 36038199 PMCID: PMC9434711 DOI: 10.1016/j.jaac.2022.04.023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 03/25/2022] [Accepted: 06/06/2022] [Indexed: 11/22/2022]
Abstract
Temperament involves stable behavioral and emotional tendencies that differ between individuals, which can be first observed in infancy or early childhood and relate to behavior in many contexts and over many years.1 One of the most rigorously characterized temperament classifications relates to the tendency of individuals to avoid the unfamiliar and to withdraw from unfamiliar people, objects, and unexpected events. This temperament is referred to as behavioral inhibition or inhibited temperament (IT).2 IT is a moderately heritable trait1 that can be measured in multiple species.3 In humans, levels of IT can be quantified from the first year of life through direct behavioral observations or reports by caregivers or teachers. Similar approaches as well as self-report questionnaires on current and/or retrospective levels of IT1 can be used later in life.
Collapse
Affiliation(s)
- Janna Marie Bas-Hoogendam
- Leiden University, Leiden, the Netherlands; Leiden University Medical Center, Leiden, the Netherlands; Leiden Institute for Brain and Cognition, Leiden, the Netherlands; National Institute of Mental Health, Bethesda, Maryland.
| | | | | | | | | | | | - Giovanni A Salum
- Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | | | | | - André Zugman
- National Institute of Mental Health, Bethesda, Maryland
| | | | - Courtney A Filippi
- National Institute of Mental Health, Bethesda, Maryland; University of Maryland, College Park
| | | | | | - Alva Tang
- University of Maryland, College Park
| | | | | | | | - Tonya White
- Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - Carl E Schwartz
- Massachusetts General Hospital, Harvard Medical School, Boston
| | | | | | | | | | | | | | | | | | | | - Shirley Y Hill
- University of Pittsburgh School of Medicine, Pennsylvania
| | - Marco Battaglia
- University of Toronto, Ontario, Canada; Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | | | | | | | | | | | | | - Jennifer Urbano Blackford
- Vanderbilt University Medical Center, Nashville, Tennessee; University of Nebraska Medical Center, Omaha
| | | | | | - Pan Liu
- Western University, London, Ontario, Canada; North Dakota State University, Fargo
| | | | | | | | | | | | - P Michiel Westenberg
- Leiden University, Leiden, the Netherlands; Leiden Institute for Brain and Cognition, Leiden, the Netherlands
| | - Nic J A van der Wee
- Leiden University Medical Center, Leiden, the Netherlands; Leiden Institute for Brain and Cognition, Leiden, the Netherlands
| | | | - Dan J Stein
- University of Cape Town, Cape Town, South Africa
| | | | - Daniel S Pine
- National Institute of Mental Health, Bethesda, Maryland
| |
Collapse
|
35
|
Cattarinussi G, Kubera KM, Hirjak D, Wolf RC, Sambataro F. Neural Correlates of the Risk for Schizophrenia and Bipolar Disorder: A Meta-analysis of Structural and Functional Neuroimaging Studies. Biol Psychiatry 2022; 92:375-384. [PMID: 35523593 DOI: 10.1016/j.biopsych.2022.02.960] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 01/28/2022] [Accepted: 02/23/2022] [Indexed: 11/19/2022]
Abstract
BACKGROUND Clinical features and genetics overlap in schizophrenia (SCZ) and bipolar disorder (BD). Identifying brain alterations associated with genetic vulnerability for SCZ and BD could help to discover intermediate phenotypes, quantifiable biological traits with greater prevalence in unaffected relatives (RELs), and early recognition biomarkers in ultrahigh risk populations. However, a comprehensive meta-analysis of structural and functional magnetic resonance imaging (MRI) studies examining relatives of patients with SCZ and BD has not been performed yet. METHODS We systematically searched PubMed, Scopus, and Web of Science for structural and functional MRI studies investigating relatives and healthy control subjects. A total of 230 eligible neuroimaging studies (6274 SCZ-RELs, 1900 BD-RELs, 10,789 healthy control subjects) were identified. We conducted coordinate-based activation likelihood estimation meta-analyses on 26 structural MRI and 81 functional MRI investigations, including stratification by task type. We also meta-analyzed regional and global volumetric changes. Finally, we performed a meta-analysis of all MRI studies combined. RESULTS Reduced thalamic volume was present in both SCZ and BD RELs. Moreover, SCZ-RELs showed alterations in corticostriatal-thalamic networks, spanning the dorsolateral prefrontal cortex and temporal regions, while BD-RELs showed altered thalamocortical and limbic regions, including the ventrolateral prefrontal, superior parietal, and medial temporal cortices, with frontoparietal alterations in RELs of BD type I. CONCLUSIONS Familiarity for SCZ and BD is associated with alterations in the thalamocortical circuits, which may be the expression of the shared genetic mechanism underlying both disorders. Furthermore, the involvement of different prefrontocortical and temporal nodes may be associated with a differential symptom expression in the two disorders.
Collapse
Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience, Università degli studi di Padova, Padova, Italy; Padova Neuroscience Center, Università degli studi di Padova, Padova, Italy
| | - Katharina M Kubera
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Robert C Wolf
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Fabio Sambataro
- Department of Neuroscience, Università degli studi di Padova, Padova, Italy; Padova Neuroscience Center, Università degli studi di Padova, Padova, Italy.
| |
Collapse
|
36
|
Macêdo MA, Sato JR, Bressan RA, Pan PM. Adolescent depression and resting-state fMRI brain networks: a scoping review of longitudinal studies. REVISTA BRASILEIRA DE PSIQUIATRIA (SAO PAULO, BRAZIL : 1999) 2022; 44. [PMID: 35896034 PMCID: PMC9375668 DOI: 10.47626/1516-4446-2021-2032] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 12/02/2021] [Indexed: 11/24/2022]
Abstract
The neurobiological factors associated with the emergence of major depressive disorder (MDD) in adolescence are still unclear. Previous cross-sectional studies have documented aberrant connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) networks. However, whether these findings precede MDD onset has not been established. This scoping review mapped key methodological aspects and main findings of longitudinal rs-fMRI studies of MDD in adolescence. Three sets of neuroimaging methods to analyze rs-fMRI data were identified: seed-based analysis, independent component analysis, and network-based approaches. Main findings involved aberrant connectivity within and between the default mode network (DMN), the cognitive control network (CCN), and the salience network (SN). Accordingly, we utilized Menon's (2011) triple-network model for neuropsychiatric disorders to summarize key results. Adolescent MDD was associated with hyperconnectivity within the SN and between DMN and SN, as well as hypoconectivity within the CCN. These findings suggested that dysfunctional connectivity among the three main large-scale brain networks preceded MDD onset. However, there was high heterogeneity in neuroimaging methods and sampling procedures, which may limit comparisons between studies. Future studies should consider some level of harmonization for clinical instruments and neuroimaging methods.
Collapse
Affiliation(s)
- Marcos Antônio Macêdo
- Laboratório Interdisciplinar de Neurociências Clínicas, Departamento de Psiquiatria, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
| | - João Ricardo Sato
- Centro de Matemática, Computação e Cognição, Universidade Federal do ABC, Santo André, SP, Brazil
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Rodrigo A. Bressan
- Laboratório Interdisciplinar de Neurociências Clínicas, Departamento de Psiquiatria, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
- Instituto Nacional de Psiquiatria do Desenvolvimento, São Paulo, SP, Brazil
| | - Pedro Mario Pan
- Laboratório Interdisciplinar de Neurociências Clínicas, Departamento de Psiquiatria, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil
- Instituto Nacional de Psiquiatria do Desenvolvimento, São Paulo, SP, Brazil
- Programa Jovens Lideranças Médicas, Academia Nacional de Medicina, Rio de Janeiro, RJ, Brazil
- Departamento de Psiquiatria, UNIFESP, São Paulo, SP, Brazil
| |
Collapse
|
37
|
Owens-Walton C, Adamson C, Walterfang M, Hall S, van Westen D, Hansson O, Shaw M, Looi JCL. Midsagittal corpus callosal thickness and cognitive impairment in Parkinson's disease. Eur J Neurosci 2022; 55:1859-1872. [PMID: 35274408 PMCID: PMC9314988 DOI: 10.1111/ejn.15640] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 02/27/2022] [Accepted: 02/28/2022] [Indexed: 11/27/2022]
Abstract
People diagnosed with Parkinson's disease (PD) can experience significant neuropsychiatric symptoms, including cognitive impairment and dementia, the neuroanatomical substrates of which are not fully characterised. Symptoms associated with cognitive impairment and dementia in PD may relate to direct structural changes to the corpus callosum via primary white matter pathology, or as a secondary outcome due to the degeneration of cortical regions. Using magnetic resonance imaging, the corpus callosum can be investigated at the midsagittal plane, where it converges to a contiguous mass and is not intertwined with other tracts. The objective of this project was thus twofold; first, we investigated possible changes in the thickness of the midsagittal callosum and cortex in patients with PD with varying levels of cognitive impairment; and secondly, we investigated the relationship between the thickness of the midsagittal corpus callosum and the thickness of the cortex. Study participants included cognitively unimpaired PD participants (n = 35), PD participants with mild cognitive impairment (n = 22), PD participants with dementia (n = 17) and healthy controls (n = 27). We found thinning of the callosum in PD-related dementia compared to PD-related mild cognitive impairment and cognitively unimpaired PD participants. Regression analyses found thickness of the left medial orbitofrontal cortex to be positively correlated with thickness of the anterior callosum in PD-related mild cognitive impairment. This study suggests that a midsagittal thickness model can uncover changes to the corpus callosum in PD-related dementia, which occur in line with changes to the cortex in this advanced disease stage.
Collapse
Affiliation(s)
- Conor Owens-Walton
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Medical School, Australian National University, Canberra, Australia.,Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Neuroinformatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, United States of America
| | - Chris Adamson
- Developmental Imaging, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Mark Walterfang
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia.,Florey Institute of Neurosciences and Mental Health, University of Melbourne, Melbourne, Australia
| | - Sara Hall
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.,Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Danielle van Westen
- Centre for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden.,Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Oskar Hansson
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.,Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Marnie Shaw
- College of Engineering and Computer Science, The Australian National University, Canberra, Australia
| | - Jeffrey C L Looi
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Medical School, Australian National University, Canberra, Australia
| |
Collapse
|
38
|
Zhang X, Suo X, Yang X, Lai H, Pan N, He M, Li Q, Kuang W, Wang S, Gong Q. Structural and functional deficits and couplings in the cortico-striato-thalamo-cerebellar circuitry in social anxiety disorder. Transl Psychiatry 2022; 12:26. [PMID: 35064097 PMCID: PMC8782859 DOI: 10.1038/s41398-022-01791-7] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 12/21/2021] [Accepted: 01/07/2022] [Indexed: 02/07/2023] Open
Abstract
Although functional and structural abnormalities in brain regions involved in the neurobiology of fear and anxiety have been observed in patients with social anxiety disorder (SAD), the findings have been heterogeneous due to small sample sizes, demographic confounders, and methodological differences. Besides, multimodal neuroimaging studies on structural-functional deficits and couplings are rather scarce. Herein, we aimed to explore functional network anomalies in brain regions with structural deficits and the effects of structure-function couplings on the SAD diagnosis. High-resolution structural magnetic resonance imaging (MRI) and resting-state functional MRI images were obtained from 49 non-comorbid patients with SAD and 53 demography-matched healthy controls. Whole-brain voxel-based morphometry analysis was conducted to investigate structural alterations, which were subsequently used as seeds for the resting-state functional connectivity analysis. In addition, correlation and mediation analyses were performed to probe the potential roles of structural-functional deficits in SAD diagnosis. SAD patients had significant gray matter volume reductions in the bilateral putamen, right thalamus, and left parahippocampus. Besides, patients with SAD demonstrated widespread resting-state dysconnectivity in cortico-striato-thalamo-cerebellar circuitry. Moreover, dysconnectivity of the putamen with the cerebellum and the right thalamus with the middle temporal gyrus/supplementary motor area partially mediated the effects of putamen/thalamus atrophy on the SAD diagnosis. Our findings provide preliminary evidence for the involvement of structural and functional deficits in cortico-striato-thalamo-cerebellar circuitry in SAD, and may contribute to clarifying the underlying mechanisms of structure-function couplings for SAD. Therefore, they could offer insights into the neurobiological substrates of SAD.
Collapse
Affiliation(s)
- Xun Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Xun Yang
- School of Public Affairs, Chongqing University, Chongqing, 400044, China
| | - Han Lai
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Min He
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Qingyuan Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Song Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, 610041, China.
- Functional & Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, 610041, China.
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, 610041, China.
- Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, 361000, China.
| |
Collapse
|
39
|
Pszczolkowski S, Cottam WJ, Briley PM, Iwabuchi SJ, Kaylor-Hughes C, Shalabi A, Babourina-Brooks B, Berrington A, Barber S, Suazo Di Paola A, Blamire A, McAllister-Williams RH, Parikh J, Abdelghani M, Matthäus L, Hauffe R, Liddle P, Auer DP, Morriss R. Connectivity-Guided Theta Burst Transcranial Magnetic Stimulation Versus Repetitive Transcranial Magnetic Stimulation for Treatment-Resistant Moderate to Severe Depression: Magnetic Resonance Imaging Protocol and SARS-CoV-2-Induced Changes for a Randomized Double-blind Controlled Trial. JMIR Res Protoc 2022; 11:e31925. [PMID: 35049517 PMCID: PMC8814922 DOI: 10.2196/31925] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 08/16/2021] [Indexed: 11/13/2022] Open
Abstract
Background Depression is a substantial health and economic burden. In approximately one-third of patients, depression is resistant to first-line treatment; therefore, it is essential to find alternative treatments. Transcranial magnetic stimulation (TMS) is a neuromodulatory treatment involving the application of magnetic pulses to the brain that is approved in the United Kingdom and the United States in treatment-resistant depression. This trial aims to compare the clinical effectiveness, cost-effectiveness, and mechanism of action of standard treatment repetitive TMS (rTMS) targeted at the F3 electroencephalogram site with a newer treatment—a type of TMS called theta burst stimulation (TBS) targeted based on measures of functional brain connectivity. This protocol outlines brain imaging acquisition and analysis for the Brain Imaging Guided Transcranial Magnetic Stimulation in Depression (BRIGhTMIND) study trial that is used to create personalized TMS targets and answer the proposed mechanistic hypotheses. Objective The aims of the imaging arm of the BRIGhTMIND study are to identify functional and neurochemical brain signatures indexing the treatment mechanisms of rTMS and connectivity-guided intermittent theta burst TMS and to identify imaging-based markers predicting response to treatment. Methods The study is a randomized double-blind controlled trial with 1:1 allocation to either 20 sessions of TBS or standard rTMS. Multimodal magnetic resonance imaging (MRI) is acquired for each participant at baseline (before TMS treatment) with T1-weighted and task-free functional MRI during rest used to estimate TMS targets. For participants enrolled in the mechanistic substudy, additional diffusion-weighted sequences are acquired at baseline and at posttreatment follow-up 16 weeks after treatment randomization. Core data sets of T1-weighted and task-free functional MRI during rest are acquired for all participants and are used to estimate TMS targets. Additional sequences of arterial spin labeling, magnetic resonance spectroscopy, and diffusion-weighted images are acquired depending on the recruitment site for mechanistic evaluation. Standard rTMS treatment is targeted at the F3 electrode site over the left dorsolateral prefrontal cortex, whereas TBS treatment is guided using the coordinate of peak effective connectivity from the right anterior insula to the left dorsolateral prefrontal cortex. Both treatment targets benefit from the level of MRI guidance, but only TBS is provided with precision targeting based on functional brain connectivity. Results Recruitment began in January 2019 and is ongoing. Data collection is expected to continue until January 2023. Conclusions This trial will determine the impact of precision MRI guidance on rTMS treatment and assess the neural mechanisms underlying this treatment in treatment-resistant depressed patients. Trial Registration ISRCTN Registry ISRCTN19674644; https://www.isrctn.com/ISRCTN19674644 International Registered Report Identifier (IRRID) DERR1-10.2196/31925
Collapse
Affiliation(s)
- Stefan Pszczolkowski
- NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom.,Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - William J Cottam
- NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom.,Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom
| | - Paul M Briley
- Institute of Mental Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom.,Nottinghamshire Healthcare NHS Foundation Trust, Nottingham, United Kingdom
| | - Sarina J Iwabuchi
- Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Catherine Kaylor-Hughes
- Institute of Mental Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Abdulrhman Shalabi
- Institute of Mental Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom.,Faculty of Medicine, University of Jeddah, Jeddah, Saudi Arabia
| | - Ben Babourina-Brooks
- NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom
| | - Adam Berrington
- Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom
| | - Shaun Barber
- Leicester Clinical Trials Unit, University of Leicester, Leicester, United Kingdom
| | - Ana Suazo Di Paola
- Leicester Clinical Trials Unit, University of Leicester, Leicester, United Kingdom
| | - Andrew Blamire
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - R Hamish McAllister-Williams
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom.,Cumbria, Northumberland, Tyne and Wear NHS Foundation Trust, Newcastle upon Tyne, United Kingdom
| | - Jehill Parikh
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | | | - Lars Matthäus
- eemagine Medical Imaging Solutions GmbH, Berlin, Germany
| | - Ralf Hauffe
- eemagine Medical Imaging Solutions GmbH, Berlin, Germany
| | - Peter Liddle
- Institute of Mental Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Dorothee P Auer
- NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom.,Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, United Kingdom.,Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom
| | - Richard Morriss
- NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom.,Institute of Mental Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom.,NIHR MindTech MedTech and in Vitro Centre, Nottingham, United Kingdom.,NIHR Applied Research Collaboration East Midlands, Nottingham, United Kingdom
| |
Collapse
|
40
|
Turner JA, Calhoun VD, Thompson PM, Jahanshad N, Ching CRK, Thomopoulos SI, Verner E, Strauss GP, Ahmed AO, Turner MD, Basodi S, Ford JM, Mathalon DH, Preda A, Belger A, Mueller BA, Lim KO, van Erp TGM. ENIGMA + COINSTAC: Improving Findability, Accessibility, Interoperability, and Re-usability. Neuroinformatics 2022; 20:261-275. [PMID: 34846691 PMCID: PMC9149142 DOI: 10.1007/s12021-021-09559-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/19/2021] [Indexed: 01/07/2023]
Abstract
The FAIR principles, as applied to clinical and neuroimaging data, reflect the goal of making research products Findable, Accessible, Interoperable, and Reusable. The use of the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymized Computation (COINSTAC) platform in the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium combines the technological approach of decentralized analyses with the sociological approach of sharing data. In addition, ENIGMA + COINSTAC provides a platform to facilitate the use of machine-actionable data objects. We first present how ENIGMA and COINSTAC support the FAIR principles, and then showcase their integration with a decentralized meta-analysis of sex differences in negative symptom severity in schizophrenia, and finally present ongoing activities and plans to advance FAIR principles in ENIGMA + COINSTAC. ENIGMA and COINSTAC currently represent efforts toward improved Access, Interoperability, and Reusability. We highlight additional improvements needed in these areas, as well as future connections to other resources for expanded Findability.
Collapse
Affiliation(s)
- Jessica A Turner
- Psychology Department, Georgia State University, Atlanta, GA, USA.
| | - Vince D Calhoun
- Psychology Department, Georgia State University, Atlanta, GA, USA
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, 30303, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Christopher R K Ching
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Eric Verner
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, 30303, USA
| | - Gregory P Strauss
- Departments of Psychology and Neuroscience, University of Georgia, Athens, GA, USA
| | - Anthony O Ahmed
- Weill Cornell Medicine, Department of Psychiatry, White Plains, NY, 10605, USA
| | - Matthew D Turner
- Psychology Department, Georgia State University, Atlanta, GA, USA
| | - Sunitha Basodi
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, 30303, USA
| | - Judith M Ford
- Veterans Affairs San Francisco Healthcare System, San Francisco, CA, 94121, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, 94121, USA
| | - Daniel H Mathalon
- Veterans Affairs San Francisco Healthcare System, San Francisco, CA, 94121, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, 94121, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, University of California Irvine Medical Center, 101 The City Drive S, Orange, CA, 92868, USA
| | - Aysenil Belger
- Department of Psychiatry and Frank Porter Graham Child Development Institute, University of North Carolina at Chapel Hill, 105 Smith Level Road, Chapel Hill, NC, 27599-8180, USA
| | - Bryon A Mueller
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Kelvin O Lim
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, 55414, USA
| | - Theo G M van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, 5251 California Ave, Irvine, CA, 92617, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, 309 Qureshey Research Lab, Irvine, CA, 92697, USA
| |
Collapse
|
41
|
Tahmasian M, Aleman A, Andreassen OA, Arab Z, Baillet M, Benedetti F, Bresser T, Bright J, Chee MW, Chylinski D, Cheng W, Deantoni M, Dresler M, Eickhoff SB, Eickhoff CR, Elvsåshagen T, Feng J, Foster-Dingley JC, Ganjgahi H, Grabe HJ, Groenewold NA, Ho TC, Hong SB, Houenou J, Irungu B, Jahanshad N, Khazaie H, Kim H, Koshmanova E, Kocevska D, Kochunov P, Lakbila-Kamal O, Leerssen J, Li M, Luik AI, Muto V, Narbutas J, Nilsonne G, O’Callaghan VS, Olsen A, Osorio RS, Poletti S, Poudel G, Reesen JE, Reneman L, Reyt M, Riemann D, Rosenzweig I, Rostampour M, Saberi A, Schiel J, Schmidt C, Schrantee A, Sciberras E, Silk TJ, Sim K, Smevik H, Soares JC, Spiegelhalder K, Stein DJ, Talwar P, Tamm S, Teresi GI, Valk SL, Van Someren E, Vandewalle G, Van Egroo M, Völzke H, Walter M, Wassing R, Weber FD, Weihs A, Westlye LT, Wright MJ, Wu MJ, Zak N, Zarei M. ENIGMA-Sleep: Challenges, opportunities, and the road map. J Sleep Res 2021; 30:e13347. [PMID: 33913199 PMCID: PMC8803276 DOI: 10.1111/jsr.13347] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 03/14/2021] [Accepted: 03/16/2021] [Indexed: 12/26/2022]
Abstract
Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, including modest sample sizes, heterogeneous clinical characteristics and varied methodologies. These issues call for a large-scale multi-centre effort in sleep research, in order to increase the number of samples, and harmonize the methods of data collection, preprocessing and analysis using pre-registered well-established protocols. The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium provides a powerful collaborative framework for combining datasets across individual sites. Recently, we have launched the ENIGMA-Sleep working group with the collaboration of several institutes from 15 countries to perform large-scale worldwide neuroimaging and genetics studies for better understanding the neurobiology of impaired sleep quality in population-based healthy individuals, the neural consequences of sleep deprivation, pathophysiology of sleep disorders, as well as neural correlates of sleep disturbances across various neuropsychiatric disorders. In this introductory review, we describe the details of our currently available datasets and our ongoing projects in the ENIGMA-Sleep group, and discuss both the potential challenges and opportunities of a collaborative initiative in sleep medicine.
Collapse
Affiliation(s)
- Masoud Tahmasian
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - André Aleman
- University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Ole A. Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Inst of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Zahra Arab
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Marion Baillet
- GIGA-Institute, Cyclotron Research Center/In Vivo Imaging, Sleep and Chronobiology Lab, University of Liège, Liège, Belgium
| | - Francesco Benedetti
- Psychiatry & Clinical Psychobiology, Division of Neuroscience, IRCCS Scientific Institute Ospedale San Raffaele, Milano, Italy
- Vita-Salute San Raffaele University, Milano, Italy
| | - Tom Bresser
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Joanna Bright
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Michael W.L. Chee
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Daphne Chylinski
- GIGA-Institute, Cyclotron Research Center/In Vivo Imaging, Sleep and Chronobiology Lab, University of Liège, Liège, Belgium
| | - Wei Cheng
- Institute of Science and Technology for Brain-inspired intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, Shanghai, China
| | - Michele Deantoni
- GIGA-Institute, Cyclotron Research Center/In Vivo Imaging, Sleep and Chronobiology Lab, University of Liège, Liège, Belgium
| | - Martin Dresler
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Simon B. Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty,, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Claudia R. Eickhoff
- Institute of Neuroscience and Medicine, Structural and functional organisation of the brain (INM-1), Research Centre Jülich, Jülich, Germany
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Torbjørn Elvsåshagen
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-inspired intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education, Fudan University, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Jessica C. Foster-Dingley
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
| | - Habib Ganjgahi
- Department of Statistics, University of Oxford, Oxford, UK
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Nynke A. Groenewold
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Tiffany C. Ho
- Department of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Seung Bong Hong
- Department of Neurology, Samsung Medical Center, SBRI (Samsung Biomedical Research Institute), Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Josselin Houenou
- Univ Paris Saclay, NeuroSpin neuroimaging platform, Psychiatry Team, UNIACT Lab, CEA Saclay, Gif-Sur-Yvette Cedex, France
- DMU IMPACT de Psychiatrie et d'Addictologie, APHP, Hôpitaux Universitaires Mondor, Créteil, France
- Univ Paris Est Créteil, INSERM U 955, IMRB Team 15 « Translational Neuropsychiatry », Foundation FondaMental, Créteil, France
| | - Benson Irungu
- Department of Psychiatry & Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Habibolah Khazaie
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Hosung Kim
- Laboratory of Neuro Imaging at USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Ekaterina Koshmanova
- GIGA-Institute, Cyclotron Research Center/In Vivo Imaging, Sleep and Chronobiology Lab, University of Liège, Liège, Belgium
| | - Desi Kocevska
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
| | - Peter Kochunov
- Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Oti Lakbila-Kamal
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Jeanne Leerssen
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Meng Li
- Clinical Affective Neuroimaging Laboratory, Otto von Guericke University, Magdeburg, Germany
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Annemarie I. Luik
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Vincenzo Muto
- GIGA-Institute, Cyclotron Research Center/In Vivo Imaging, Sleep and Chronobiology Lab, University of Liège, Liège, Belgium
| | - Justinas Narbutas
- GIGA-Institute, Cyclotron Research Center/In Vivo Imaging, Sleep and Chronobiology Lab, University of Liège, Liège, Belgium
| | - Gustav Nilsonne
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Psychology, Stress Research Institute, Stockholm University, Stockholm, Sweden
| | | | - Alexander Olsen
- Department of Physical Medicine and Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Ricardo S. Osorio
- Healthy Brain Aging and Sleep Center, Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
- Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Sara Poletti
- Psychiatry & Clinical Psychobiology, Division of Neuroscience, IRCCS Scientific Institute Ospedale San Raffaele, Milano, Italy
- Vita-Salute San Raffaele University, Milano, Italy
| | - Govinda Poudel
- Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, Vic., Australia
| | - Joyce E. Reesen
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Liesbeth Reneman
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, AMC, Amsterdam, The Netherlands
| | - Mathilde Reyt
- GIGA-Institute, Cyclotron Research Center/In Vivo Imaging, Sleep and Chronobiology Lab, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
| | - Dieter Riemann
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
| | - Ivana Rosenzweig
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King’s College London, London, UK
- Sleep Disorders Centre, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Masoumeh Rostampour
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Amin Saberi
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Julian Schiel
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
| | - Christina Schmidt
- GIGA-Institute, Cyclotron Research Center/In Vivo Imaging, Sleep and Chronobiology Lab, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, AMC, Amsterdam, The Netherlands
| | - Emma Sciberras
- Department of Paediatrics, University of Melbourne, Parkville, Vic., Australia
- Murdoch Children's Research Institute, Parkville, Vic., Australia
- School of Psychology, Deakin University, Geelong, Vic., Australia
| | - Tim J. Silk
- Department of Paediatrics, University of Melbourne, Parkville, Vic., Australia
- Murdoch Children's Research Institute, Parkville, Vic., Australia
- School of Psychology, Deakin University, Geelong, Vic., Australia
| | - Kang Sim
- Institute of Mental Health, Buangkok, Singapore
| | - Hanne Smevik
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway
| | - Jair C. Soares
- Department of Psychiatry & Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Kai Spiegelhalder
- Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany
| | - Dan J. Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Puneet Talwar
- GIGA-Institute, Cyclotron Research Center/In Vivo Imaging, Sleep and Chronobiology Lab, University of Liège, Liège, Belgium
| | - Sandra Tamm
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Psychology, Stress Research Institute, Stockholm University, Stockholm, Sweden
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Giana I. Teresi
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Sofie L. Valk
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty,, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Eus Van Someren
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience (NIN), an Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR), Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
- Vrije Universiteit, Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, The Netherlands
| | - Gilles Vandewalle
- GIGA-Institute, Cyclotron Research Center/In Vivo Imaging, Sleep and Chronobiology Lab, University of Liège, Liège, Belgium
| | - Maxime Van Egroo
- GIGA-Institute, Cyclotron Research Center/In Vivo Imaging, Sleep and Chronobiology Lab, University of Liège, Liège, Belgium
| | - Henry Völzke
- Institute for Community Medicine, Department SHIP/Clinical Epidemiological Research, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), Greifswald, Germany
| | - Martin Walter
- Clinical Affective Neuroimaging Laboratory, Otto von Guericke University, Magdeburg, Germany
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- Department of Psychiatry and Psychotherapy, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Rick Wassing
- Department of Sleep and Circadian Research, Woolcock Institute of Medical Research, The University of Sydney, Sydney, Australia
| | - Frederik D. Weber
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Antoine Weihs
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Lars Tjelta Westlye
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Inst of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Margaret J. Wright
- Queensland Brain Institute, The University of Queensland, Brisbane, Qld, Australia
- Centre for Advanced Imaging, The University of Queensland, St Lucia, Qld, Australia
| | - Mon-Ju Wu
- Department of Psychology and Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Nathalia Zak
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Inst of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Mojtaba Zarei
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| |
Collapse
|
42
|
Axelrud LK, Simioni AR, Pine DS, Winkler AM, Pan PM, Sato JR, Zugman A, Parker N, Picon F, Jackowski A, Hoexter MQ, Barker G, Martinot JL, Martinot MLP, Satterthwaite T, Rohde LA, Milham M, Barker ED, Salum GA. Neuroimaging Association Scores: reliability and validity of aggregate measures of brain structural features linked to mental disorders in youth. Eur Child Adolesc Psychiatry 2021; 30:1895-1906. [PMID: 33030612 PMCID: PMC9077631 DOI: 10.1007/s00787-020-01653-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 09/21/2020] [Indexed: 10/23/2022]
Abstract
In genetics, aggregation of many loci with small effect sizes into a single score improved prediction. Nevertheless, studies applying easily replicable weighted scores to neuroimaging data are lacking. Our aim was to assess the reliability and validity of the Neuroimaging Association Score (NAS), which combines information from structural brain features previously linked to mental disorders. Participants were 726 youth (aged 6-14) from two cities in Brazil who underwent MRI and psychopathology assessment at baseline and 387 at 3-year follow-up. Results were replicated in two samples: IMAGEN (n = 1627) and the Healthy Brain Network (n = 843). NAS were derived by summing the product of each standardized brain feature by the effect size of the association of that brain feature with seven psychiatric disorders documented by previous meta-analyses. NAS were calculated for surface area, cortical thickness and subcortical volumes using T1-weighted scans. NAS reliability, temporal stability and psychopathology and cognition prediction were analyzed. NAS for surface area showed high internal consistency and 3-year stability and predicted general psychopathology and cognition with higher replicability than specific symptomatic domains for all samples. They also predicted general psychopathology with higher replicability than single structures alone, accounting for 1-3% of the variance, but without directionality. The NAS for cortical thickness and subcortical volumes showed lower internal consistency and less replicable associations with behavioural phenotypes. These findings indicate the NAS based on surface area might be replicable markers of general psychopathology, but these links are unlikely to be causal or clinically useful yet.
Collapse
Affiliation(s)
- Luiza Kvitko Axelrud
- Section On Negative Affect and Social Processes, Departamento de Psiquiatria e Medicina Legal, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Ramiro Barcelos, 2350, Room 2202, Porto Alegre, 90035-003, Brazil.
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil.
| | - André Rafael Simioni
- Section On Negative Affect and Social Processes, Departamento de Psiquiatria e Medicina Legal, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Ramiro Barcelos, 2350, Room 2202, Porto Alegre, 90035-003, Brazil
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
| | - Daniel Samuel Pine
- National Institute of Mental Health Intramural Research Program, Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Anderson Marcelo Winkler
- National Institute of Mental Health Intramural Research Program, Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Pedro Mario Pan
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
- Departamento de Psiquiatria, Universidade Federal de São Paulo, São Paulo, Brazil
| | - João Ricardo Sato
- Centro de Matemática, Computação E Cognição, Universidade Federal Do ABC, Santo André, Brazil
| | - André Zugman
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
- Departamento de Psiquiatria, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Nadine Parker
- Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Felipe Picon
- Section On Negative Affect and Social Processes, Departamento de Psiquiatria e Medicina Legal, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Ramiro Barcelos, 2350, Room 2202, Porto Alegre, 90035-003, Brazil
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
| | - Andrea Jackowski
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
- Departamento de Psiquiatria, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Marcelo Queiroz Hoexter
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
- Departamento de Psiquiatria, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Gareth Barker
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Jean-Luc Martinot
- Institut National de La Santé Et de La Recherche Médicale, INSERM Unit 1000 "Neuroimaging and Psychiatry", University Paris Saclay, University Paris Descartes, Paris, France
| | - Marie Laure Paillère Martinot
- Institut National de La Santé Et de La Recherche Médicale, INSERM Unit 1000 "Neuroimaging and Psychiatry", University Paris Saclay, University Paris Descartes, Paris, France
| | - Theodore Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA
| | - Luis Augusto Rohde
- Section On Negative Affect and Social Processes, Departamento de Psiquiatria e Medicina Legal, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Ramiro Barcelos, 2350, Room 2202, Porto Alegre, 90035-003, Brazil
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
| | | | - Edward Dylan Barker
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Giovanni Abrahão Salum
- Section On Negative Affect and Social Processes, Departamento de Psiquiatria e Medicina Legal, Hospital de Clínicas de Porto Alegre, Universidade Federal Do Rio Grande Do Sul, Ramiro Barcelos, 2350, Room 2202, Porto Alegre, 90035-003, Brazil
- National Institute of Developmental Psychiatry (INPD, CNPq), São Paulo, Brazil
| |
Collapse
|
43
|
Zugman A, Winkler AM, Pine DS. Recent advances in understanding neural correlates of anxiety disorders in children and adolescents. Curr Opin Psychiatry 2021; 34:617-623. [PMID: 34475352 PMCID: PMC8490291 DOI: 10.1097/yco.0000000000000743] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
PURPOSE OF REVIEW Anxiety disorders are some of the most common psychiatric diagnoses in children and adolescents, but attempts to improve outcome prediction and treatment have stalled. This review highlights recent findings on neural indices related to fear and anxiety that provide novel directions for attempts to create such improvements. RECENT FINDINGS Stimuli capable of provoking fear engage many brain regions, including the amygdala, medial prefrontal cortex, hippocampus, and bed nucleus of the stria terminalis. Studies in rodents suggest that sustained, low-level threats are particularly likely to engage the bed nucleus of the stria terminalis, which appears to malfunction in anxiety disorders. However, anxiety disorders, like most mental illnesses, appear less likely to arise from alterations in isolated brain regions than in distributed brain circuitry. Findings from large-scale studies of brain connectivity may reveal signs of such broadly distributed dysfunction, though available studies report small effect sizes. Finally, we review novel approaches with promise for using such large-scale data to detect clinically relevant, broadly distributed circuitry dysfunction. SUMMARY Recent work maps neural circuitry related to fear and anxiety. This circuitry may malfunction in anxiety disorders. Integrating findings from animal studies, big datasets, and novel analytical approaches may generate clinically relevant insights based on this recent work.
Collapse
Affiliation(s)
- Andre Zugman
- Section on Development and Affective Neuroscience, Emotion and Development Branch. National Institute of Mental Health, National Institutes of Health - Bethesda, MD
| | - Anderson M. Winkler
- Section on Development and Affective Neuroscience, Emotion and Development Branch. National Institute of Mental Health, National Institutes of Health - Bethesda, MD
| | - Daniel S. Pine
- Section on Development and Affective Neuroscience, Emotion and Development Branch. National Institute of Mental Health, National Institutes of Health - Bethesda, MD
| |
Collapse
|
44
|
Thompson PM, Jahanshad N, Schmaal L, Turner JA, Winkler AM, Thomopoulos SI, Egan GF, Kochunov P. The Enhancing NeuroImaging Genetics through Meta-Analysis Consortium: 10 Years of Global Collaborations in Human Brain Mapping. Hum Brain Mapp 2021; 43:15-22. [PMID: 34612558 PMCID: PMC8675422 DOI: 10.1002/hbm.25672] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 09/09/2021] [Accepted: 09/16/2021] [Indexed: 12/23/2022] Open
Abstract
This Special Issue of Human Brain Mapping is dedicated to a 10-year anniversary of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium. It reports updates from a broad range of international neuroimaging projects that pool data from around the world to answer fundamental questions in neuroscience. Since ENIGMA was formed in December 2009, the initiative grew into a worldwide effort with over 2,000 participating scientists from 45 countries, and over 50 working groups leading large-scale studies of human brain disorders. Over the last decade, many lessons were learned on how best to pool brain data from diverse sources. Working groups were created to develop methods to analyze worldwide data from anatomical and diffusion magnetic resonance imaging (MRI), resting state and task-based functional MRI, electroencephalography (EEG), magnetoencephalography (MEG), and magnetic resonance spectroscopy (MRS). The quest to understand genetic effects on human brain development and disease also led to analyses of brain scans on an unprecedented scale. Genetic roadmaps of the human cortex were created by researchers worldwide who collaborated to perform statistically well-powered analyses of common and rare genetic variants on brain measures and rates of brain development and aging. Here, we summarize the 31 papers in this Special Issue, covering: (a) technical approaches to harmonize analysis of different types of brain imaging data, (b) reviews of the last decade of work by several of ENIGMA's clinical and technical working groups, and (c) new empirical papers reporting large-scale international brain mapping analyses in patients with substance use disorders, schizophrenia, bipolar disorders, major depression, posttraumatic stress disorder, obsessive compulsive disorder, epilepsy, and stroke.
Collapse
Affiliation(s)
- Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Lianne Schmaal
- Orygen, Parkville, Australia.,Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Jessica A Turner
- Psychology Department, Georgia State University, Atlanta, Georgia, USA
| | - Anderson M Winkler
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Bethesda, Maryland, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Gary F Egan
- Monash Biomedical Imaging, Monash University, Melbourne, Victoria, Australia.,Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Peter Kochunov
- Department of Psychiatry, Maryland Psychiatric Research Center, University of Maryland School of Medicine, Baltimore, Maryland, USA
| |
Collapse
|
45
|
Harrewijn A, Cardinale EM, Groenewold NA, Bas-Hoogendam JM, Aghajani M, Hilbert K, Cardoner N, Porta-Casteràs D, Gosnell S, Salas R, Jackowski AP, Pan PM, Salum GA, Blair KS, Blair JR, Hammoud MZ, Milad MR, Burkhouse KL, Phan KL, Schroeder HK, Strawn JR, Beesdo-Baum K, Jahanshad N, Thomopoulos SI, Buckner R, Nielsen JA, Smoller JW, Soares JC, Mwangi B, Wu MJ, Zunta-Soares GB, Assaf M, Diefenbach GJ, Brambilla P, Maggioni E, Hofmann D, Straube T, Andreescu C, Berta R, Tamburo E, Price RB, Manfro GG, Agosta F, Canu E, Cividini C, Filippi M, Kostić M, Munjiza Jovanovic A, Alberton BAV, Benson B, Freitag GF, Filippi CA, Gold AL, Leibenluft E, Ringlein GV, Werwath KE, Zwiebel H, Zugman A, Grabe HJ, Van der Auwera S, Wittfeld K, Völzke H, Bülow R, Balderston NL, Ernst M, Grillon C, Mujica-Parodi LR, van Nieuwenhuizen H, Critchley HD, Makovac E, Mancini M, Meeten F, Ottaviani C, Ball TM, Fonzo GA, Paulus MP, Stein MB, Gur RE, Gur RC, Kaczkurkin AN, Larsen B, Satterthwaite TD, Harper J, Myers M, Perino MT, Sylvester CM, Yu Q, Lueken U, Veltman DJ, Thompson PM, Stein DJ, Van der Wee NJA, Winkler AM, Pine DS. Cortical and subcortical brain structure in generalized anxiety disorder: findings from 28 research sites in the ENIGMA-Anxiety Working Group. Transl Psychiatry 2021; 11:502. [PMID: 34599145 PMCID: PMC8486763 DOI: 10.1038/s41398-021-01622-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 09/02/2021] [Accepted: 09/14/2021] [Indexed: 12/22/2022] Open
Abstract
The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5-90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.
Collapse
Affiliation(s)
- Anita Harrewijn
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA.
| | - Elise M Cardinale
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Nynke A Groenewold
- Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Janna Marie Bas-Hoogendam
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
- Department of Developmental and Educational Psychology, Institute of Psychology, Leiden University, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Moji Aghajani
- Department of Psychiatry, Amsterdam UMC, location VUMC, Amsterdam, The Netherlands
- Department of Research & Innovation, GGZ InGeest, Amsterdam, The Netherlands
| | - Kevin Hilbert
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Narcis Cardoner
- Department of Mental Health, University Hospital Parc Taulí-I3PT, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Carlos III Health Institute, Madrid, Spain
| | - Daniel Porta-Casteràs
- Department of Mental Health, University Hospital Parc Taulí-I3PT, Barcelona, Spain
- Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Carlos III Health Institute, Madrid, Spain
| | - Savannah Gosnell
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Ramiro Salas
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Andrea P Jackowski
- LiNC, Department of Psychiatry, Federal University of São Paulo, São Paulo, Brazil
| | - Pedro M Pan
- LiNC, Department of Psychiatry, Federal University of São Paulo, São Paulo, Brazil
| | - Giovanni A Salum
- Section on Negative Affect and Social Processes, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Karina S Blair
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, USA
| | - James R Blair
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Mira Z Hammoud
- Department of Psychiatry, NYU School of Medicine, New York University, New York, NY, USA
| | - Mohammed R Milad
- Department of Psychiatry, NYU School of Medicine, New York University, New York, NY, USA
| | - Katie L Burkhouse
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - K Luan Phan
- Department of Psychiatry and Behavioral Health, The Ohio State University, Columbus, OH, USA
| | - Heidi K Schroeder
- Department of Psychiatry & Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Jeffrey R Strawn
- Department of Psychiatry & Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Katja Beesdo-Baum
- Behavioral Epidemiology, Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Randy Buckner
- Center for Brain Science & Department of Psychology, Harvard University, Cambridge, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Jared A Nielsen
- Center for Brain Science & Department of Psychology, Harvard University, Cambridge, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Psychology Department & Neuroscience Center, Brigham Young University, Provo, USA
| | - Jordan W Smoller
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Jair C Soares
- Center Of Excellence On Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Benson Mwangi
- Center Of Excellence On Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Mon-Ju Wu
- Center Of Excellence On Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Giovana B Zunta-Soares
- Center Of Excellence On Mood Disorders, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Michal Assaf
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, Hartford, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Gretchen J Diefenbach
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Anxiety Disorders Center, Institute of Living, Hartford Hospital, Hartford, CT, USA
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Eleonora Maggioni
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - David Hofmann
- Institute of Medical Psychology and Systems Neuroscience, University of Muenster, Muenster, Germany
| | - Thomas Straube
- Institute of Medical Psychology and Systems Neuroscience, University of Muenster, Muenster, Germany
| | - Carmen Andreescu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Rachel Berta
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Erica Tamburo
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Rebecca B Price
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Gisele G Manfro
- Anxiety Disorder Program, Hospital de Clínicas de Porto Alegre, Department of Psychiatry, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Elisa Canu
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Camilla Cividini
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurophysiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Milutin Kostić
- Institute of Mental Health, University of Belgrade, Belgrade, Serbia
- Department of Psychiatry, School of Medicine, University of Belgrade, Belgrade, Serbia
| | | | - Bianca A V Alberton
- Graduate Program in Electrical and Computer Engineering, Universidade Tecnológica Federal do Paraná, Curitiba, Puerto Rico, Brazil
| | - Brenda Benson
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Gabrielle F Freitag
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Courtney A Filippi
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Andrea L Gold
- Department of Psychiatry and Human Behavior, Brown University Warren Alpert Medical School, Providence, RI, USA
| | - Ellen Leibenluft
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Grace V Ringlein
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Kathryn E Werwath
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Hannah Zwiebel
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - André Zugman
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Sandra Van der Auwera
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Robin Bülow
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Nicholas L Balderston
- Center for Neuromodulation in Depression and Stress, University of Pennsylvania, Philadelphia, PA, USA
| | - Monique Ernst
- Section on Neurobiology of Fear and Anxiety, National Institute of Mental Health, Bethesda, MD, USA
| | - Christian Grillon
- Section on Neurobiology of Fear and Anxiety, National Institute of Mental Health, Bethesda, MD, USA
| | | | | | - Hugo D Critchley
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK
| | - Elena Makovac
- Centre for Neuroimaging Science, Kings College London, London, UK
| | - Matteo Mancini
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK
| | - Frances Meeten
- School of Psychology, University of Sussex, Brighton, UK
| | - Cristina Ottaviani
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- IRCCS Santa Lucia Foundation, Rome, Italy
| | - Tali M Ball
- Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Gregory A Fonzo
- Department of Psychiatry and Behavioral Sciences, The University of Texas at Austin Dell Medical School, Austin, TX, USA
| | | | - Murray B Stein
- Department of Psychiatry, School of Medicine and Herbert Wertheim School of Public Health, University of California, San Diego, La Jolla, CA, USA
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Bart Larsen
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Jennifer Harper
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Michael Myers
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Michael T Perino
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Chad M Sylvester
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Qiongru Yu
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Ulrike Lueken
- Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC, location VUMC, Amsterdam, The Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Dan J Stein
- South African Medical Research Council Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Nic J A Van der Wee
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden, The Netherlands
| | - Anderson M Winkler
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Daniel S Pine
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| |
Collapse
|
46
|
Estimating Gender and Age from Brain Structural MRI of Children and Adolescents: A 3D Convolutional Neural Network Multitask Learning Model. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2021; 2021:5550914. [PMID: 34122531 PMCID: PMC8172319 DOI: 10.1155/2021/5550914] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 04/01/2021] [Accepted: 04/24/2021] [Indexed: 01/10/2023]
Abstract
Despite recent advances, assessing biological measurements for neuropsychiatric disorders is still a challenge, where confounding variables such as gender and age (as a proxy for neurodevelopment) play an important role. This study explores brain structural magnetic resonance imaging (sMRI) from two public data sets (ABIDE-II and ADHD-200) with healthy control (HC, N = 894), autism spectrum disorder (ASD, N = 251), and attention deficit hyperactivity disorder (ADHD, N = 357) individuals. We used gray and white matter preprocessed via voxel-based morphometry (VBM) to train a 3D convolutional neural network with a multitask learning strategy to estimate gender, age, and mental health status from structural brain differences. Gradient-based methods were employed to generate attention maps, providing clinically relevant identification of most representative brain regions for models' decision-making. This approach resulted in satisfactory predictions for gender and age. ADHD-200-trained models, evaluated in 10-fold cross-validation procedures on test set, obtained a mean absolute error (MAE) of 1.43 years (±0.22 SD) for age prediction and an area under the curve (AUC) of 0.85 (±0.04 SD) for gender classification. In out-of-sample validation, the best-performing ADHD-200 models satisfactorily predicted age (MAE = 1.57 years) and gender (AUC = 0.89) in the ABIDE-II data set. The models' accuracy was in line with the current state-of-the-art machine learning applications in neuroimaging. Key regions for models' accuracy were presented as a meaningful graphical output. New implementations, such as the use of VBM along with a 3D convolutional neural network multitask learning model and a brain imaging graphical output, reinforce the relevance of the proposed workflow.
Collapse
|
47
|
Sheng L, Ma H, Yao L, Dai Z, Hu J. Consistent brain grey matter volume alterations in adult patients with panic disorder and social anxiety disorder revisited. J Affect Disord 2021; 286:120-122. [PMID: 33721738 DOI: 10.1016/j.jad.2021.02.079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 02/22/2021] [Accepted: 02/26/2021] [Indexed: 11/20/2022]
Affiliation(s)
- LiQin Sheng
- Department of Neurology, Kunshan Hospital of Traditional Chinese Medicine, Kunshan, PR China
| | - HaiRong Ma
- Department of Neurology, Kunshan Hospital of Traditional Chinese Medicine, Kunshan, PR China
| | - LiZheng Yao
- Department of Radiology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng, PR China
| | - ZhenYu Dai
- Department of Radiology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng, PR China
| | - JianBin Hu
- Department of Radiology, The Yancheng School of Clinical Medicine of Nanjing Medical University, Yancheng, PR China.
| |
Collapse
|
48
|
Kim N, Kim MJ. Altered Task-Evoked Corticolimbic Responsivity in Generalized Anxiety Disorder. Int J Mol Sci 2021; 22:ijms22073630. [PMID: 33807276 PMCID: PMC8037355 DOI: 10.3390/ijms22073630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 03/23/2021] [Accepted: 03/26/2021] [Indexed: 11/16/2022] Open
Abstract
Generalized anxiety disorder (GAD) is marked by uncontrollable, persistent worry and exaggerated response to uncertainty. Here, we review and summarize the findings from the GAD literature that employs functional neuroimaging methods. In particular, the present review focuses on task-based blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies. We find that select brain regions often regarded as a part of a corticolimbic circuit (e.g., amygdala, anterior cingulate cortex, prefrontal cortex) are consistently targeted for a priori hypothesis-driven analyses, which, in turn, shows varying degrees of abnormal BOLD responsivity in GAD. Data-driven whole-brain analyses show the insula and the hippocampus, among other regions, to be affected by GAD, depending on the task used in each individual study. Overall, while the heterogeneity of the tasks and sample size limits the generalizability of the findings thus far, some promising convergence can be observed in the form of the altered BOLD responsivity of the corticolimbic circuitry in GAD.
Collapse
Affiliation(s)
- Nayoung Kim
- Department of Psychology, Sungkyunkwan University, Seoul 03063, Korea;
| | - M. Justin Kim
- Department of Psychology, Sungkyunkwan University, Seoul 03063, Korea;
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon 16060, Korea
- Correspondence:
| |
Collapse
|
49
|
Sämann PG, Iglesias JE, Gutman B, Grotegerd D, Leenings R, Flint C, Dannlowski U, Clarke‐Rubright EK, Morey RA, Erp TG, Whelan CD, Han LKM, Velzen LS, Cao B, Augustinack JC, Thompson PM, Jahanshad N, Schmaal L. FreeSurfer
‐based segmentation of hippocampal subfields: A review of methods and applications, with a novel quality control procedure for
ENIGMA
studies and other collaborative efforts. Hum Brain Mapp 2020; 43:207-233. [PMID: 33368865 PMCID: PMC8805696 DOI: 10.1002/hbm.25326] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 11/26/2020] [Accepted: 12/13/2020] [Indexed: 12/11/2022] Open
Abstract
Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and variation in hippocampal measures is related to cognitive performance and other complex phenotypes such as stress sensitivity. Hippocampal subregions are increasingly studied, as automated algorithms have become available for mapping and volume quantification. In the context of the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with neurological and psychiatric conditions along with data from matched controls. In this overview, we explain the algorithm's principles, summarize measurement reliability studies, and demonstrate two additional aspects (subfield autocorrelation and volume/reliability correlation) with illustrative data. We then explain the rationale for a standardized hippocampal subfield segmentation quality control (QC) procedure for improved pipeline harmonization. To guide researchers to make optimal use of the algorithm, we discuss how global size and age effects can be modeled, how QC steps can be incorporated and how subfields may be aggregated into composite volumes. This discussion is based on a synopsis of 162 published neuroimaging studies (01/2013–12/2019) that applied the FreeSurfer hippocampal subfield segmentation in a broad range of domains including cognition and healthy aging, brain development and neurodegeneration, affective disorders, psychosis, stress regulation, neurotoxicity, epilepsy, inflammatory disease, childhood adversity and posttraumatic stress disorder, and candidate and whole genome (epi‐)genetics. Finally, we highlight points where FreeSurfer‐based hippocampal subfield studies may be optimized.
Collapse
Affiliation(s)
| | - Juan Eugenio Iglesias
- Centre for Medical Image Computing University College London London UK
- The Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital/Harvard Medical School Boston Massachusetts US
- Computer Science and AI Laboratory (CSAIL), Massachusetts Institute of Technology (MIT) Cambridge Massachusetts US
| | - Boris Gutman
- Department of Biomedical Engineering Illinois Institute of Technology Chicago USA
| | | | - Ramona Leenings
- Department of Psychiatry University of Münster Münster Germany
| | - Claas Flint
- Department of Psychiatry University of Münster Münster Germany
- Department of Mathematics and Computer Science University of Münster Germany
| | - Udo Dannlowski
- Department of Psychiatry University of Münster Münster Germany
| | - Emily K. Clarke‐Rubright
- Brain Imaging and Analysis Center, Duke University Durham North Carolina USA
- VISN 6 MIRECC, Durham VA Durham North Carolina USA
| | - Rajendra A. Morey
- Brain Imaging and Analysis Center, Duke University Durham North Carolina USA
- VISN 6 MIRECC, Durham VA Durham North Carolina USA
| | - Theo G.M. Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior University of California Irvine California USA
- Center for the Neurobiology of Learning and Memory University of California Irvine Irvine California USA
| | - Christopher D. Whelan
- Imaging Genetics Center Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California Los Angeles California USA
| | - Laura K. M. Han
- Department of Psychiatry Amsterdam University Medical Centers, Vrije Universiteit and GGZ inGeest, Amsterdam Neuroscience Amsterdam The Netherlands
| | - Laura S. Velzen
- Orygen Parkville Australia
- Centre for Youth Mental Health The University of Melbourne Melbourne Australia
| | - Bo Cao
- Department of Psychiatry, Faculty of Medicine & Dentistry University of Alberta Edmonton Canada
| | - Jean C. Augustinack
- The Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital/Harvard Medical School Boston Massachusetts US
| | - Paul M. Thompson
- Imaging Genetics Center Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California Los Angeles California USA
| | - Neda Jahanshad
- Imaging Genetics Center Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California Los Angeles California USA
| | - Lianne Schmaal
- Orygen Parkville Australia
- Centre for Youth Mental Health The University of Melbourne Melbourne Australia
| |
Collapse
|