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Archer C, Jeong HJ, Reimann GE, Durham EL, Moore TM, Wang S, Ashar DA, Kaczkurkin AN. Concurrent and longitudinal neurostructural correlates of irritability in children. Neuropsychopharmacology 2024; 49:2069-2076. [PMID: 39154134 PMCID: PMC11480493 DOI: 10.1038/s41386-024-01966-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 08/02/2024] [Accepted: 08/08/2024] [Indexed: 08/19/2024]
Abstract
Irritability, or an increased proneness to frustration and anger, is common in youth; however, few studies have examined neurostructural correlates of irritability in children. The purpose of the current study was to examine concurrent and longitudinal associations between brain structure and irritability in a large sample of 9-10-year-old children. Participants included 10,647 children from the Adolescent Brain Cognitive Developmentsm Study (ABCD Study®). We related a latent irritability factor to gray matter volume, cortical thickness, and surface area in 68 cortical regions and to gray matter volume in 19 subcortical regions using structural equation modeling. Multiple comparisons were adjusted for using the false discovery rate (FDR). After controlling for age, sex, race/ethnicity, scanner model, parent's highest level of education, medication use, and total intracranial volume, irritability was associated with smaller volumes in primarily temporal and parietal regions at baseline. Longitudinal analyses showed that baseline gray matter volume did not predict irritability symptoms at the 3rd-year follow-up. No significant associations were found for cortical thickness or surface area. The current study demonstrates inverse associations between irritability and volume in regions implicated in emotional processing/social cognition, attention allocation, and movement/perception. We advance prior research by demonstrating that neurostructural differences associated with irritability are already apparent by age 9-10 years, extending this work to children and supporting theories positing socioemotional deficits as a key feature of irritability.
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Affiliation(s)
- Camille Archer
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | - Hee Jung Jeong
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | | | | | - Tyler M Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Shuti Wang
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | - Devisi A Ashar
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
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Parker AJ, Walker JC, Jordan LS, Takarae Y, Wiggins JL, Dougherty LR. Neural mechanisms of inhibitory control in preadolescent irritability: Insights from the ABCD study. Biol Psychol 2024; 192:108856. [PMID: 39154835 PMCID: PMC11464202 DOI: 10.1016/j.biopsycho.2024.108856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 07/19/2024] [Accepted: 08/13/2024] [Indexed: 08/20/2024]
Abstract
OBJECTIVE Elevated pediatric irritability is a transdiagnostic symptom that predicts multiple mental health problems in adolescence and adulthood. Altered top-down regulatory networks, such as inhibitory control networks that suppress an impulse in favor of goal-directed behavior, are thought to contribute to high levels of youth irritability. Nevertheless, little work has examined links between youth irritability and neural processes supporting inhibitory control in large diverse samples, nor have they focused on the key period ramping up to adolescence (i.e., preadolescence). METHOD Functional MRI data from 5380 preadolescents (age M=9.97 years, SD=0.62) in the baseline Adolescent Brain and Cognitive Development (ABCD) Study were analyzed. Parents reported on their preadolescent's irritability. The stop signal task (SST) was leveraged to probe successful and failed inhibitory control. Activation and functional connectivity with amygdala, ventral striatum, and prefrontal seed regions were calculated during the SST and used in whole brain and region of interest (ROI) group-level analyses evaluating irritability effects. RESULTS Preadolescents with higher levels of irritability displayed decreases in functional connectivity among amygdala, ventral striatum, and prefrontal cortex regions during both successful and failed inhibitory control conditions. These results remained after adjusting for co-occurring anxiety, depression, and attention-deficit/hyperactivity symptoms. CONCLUSIONS Findings suggest neural aberrations in inhibitory control play a role in the pathophysiology of preadolescent irritability and associations are not merely due to co-occurring symptoms. Neural mechanisms of inhibitory control associated with irritability may provide novel intervention targets.
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Affiliation(s)
- Alyssa J Parker
- Department of Psychology, University of Maryland, College Park, United States.
| | - Johanna C Walker
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, United States
| | - Leslie S Jordan
- Department of Psychology, University of Maryland, College Park, United States; Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, United States; Institute for Clinical & Translational Research (ICTR), University of Maryland Baltimore, United States
| | - Yukari Takarae
- Department of Psychology, San Diego State University, United States
| | - Jillian Lee Wiggins
- Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, United States; Department of Psychology, San Diego State University, United States
| | - Lea R Dougherty
- Department of Psychology, University of Maryland, College Park, United States
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3
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Elvin OM, Modecki KL, Waters AM. An Expanded Conceptual Framework for Understanding Irritability in Childhood: The Role of Cognitive Control Processes. Clin Child Fam Psychol Rev 2024; 27:381-406. [PMID: 38856946 PMCID: PMC11222227 DOI: 10.1007/s10567-024-00489-0] [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: 05/08/2024] [Indexed: 06/11/2024]
Abstract
Children prone to irritability experience significant functional impairments and internalising and externalising problems. Contemporary models have sought to elucidate the underlying mechanisms in irritability, such as aberrant threat and reward biases to improve interventions. However, the cognitive control processes that underlie threat (e.g., attention towards threats) and reward (e.g., attention towards reward-related cues) biases and the factors which influence the differential activation of positive and negative valence systems and thus leading to maladaptive activation of cognitive control processes (i.e., proactive and reactive control) are unclear. Thus, we aim to integrate extant theoretical and empirical research to elucidate the cognitive control processes underlying threat and reward processing that contribute to irritability in middle childhood and provide a guiding framework for future research and treatment. We propose an expanded conceptual framework of irritability that includes broad intraindividual and environmental vulnerability factors and propose proximal 'setting' factors that activate the negative valence and positive valence systems and proactive and reactive cognitive control processes which underpin the expression and progression of irritability. We consider the implications of this expanded conceptualisation of irritability and provide suggestions for future research.
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Affiliation(s)
- Olivia M Elvin
- School of Applied Psychology, Griffith University, Mount Gravatt Campus, Brisbane, QLD, Australia.
| | - Kathryn L Modecki
- Centre for Mental Health and School of Applied Psychology, Griffith University, Mount Gravatt Campus, Brisbane, QLD, Australia
- School of Psychological Science, University of Western Australia & Telethon Kids Institute, Perth, Australia
| | - Allison M Waters
- Centre for Mental Health and School of Applied Psychology, Griffith University, Mount Gravatt Campus, Brisbane, QLD, Australia.
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Yang J, Huggins AA, Sun D, Baird CL, Haswell CC, Frijling JL, Olff M, van Zuiden M, Koch SBJ, Nawijn L, Veltman DJ, Suarez-Jimenez B, Zhu X, Neria Y, Hudson AR, Mueller SC, Baker JT, Lebois LAM, Kaufman ML, Qi R, Lu GM, Říha P, Rektor I, Dennis EL, Ching CRK, Thomopoulos SI, Salminen LE, Jahanshad N, Thompson PM, Stein DJ, Koopowitz SM, Ipser JC, Seedat S, du Plessis S, van den Heuvel LL, Wang L, Zhu Y, Li G, Sierk A, Manthey A, Walter H, Daniels JK, Schmahl C, Herzog JI, Liberzon I, King A, Angstadt M, Davenport ND, Sponheim SR, Disner SG, Straube T, Hofmann D, Grupe DW, Nitschke JB, Davidson RJ, Larson CL, deRoon-Cassini TA, Blackford JU, Olatunji BO, Gordon EM, May G, Nelson SM, Abdallah CG, Levy I, Harpaz-Rotem I, Krystal JH, Morey RA, Sotiras A. Examining the association between posttraumatic stress disorder and disruptions in cortical networks identified using data-driven methods. Neuropsychopharmacology 2024; 49:609-619. [PMID: 38017161 PMCID: PMC10789873 DOI: 10.1038/s41386-023-01763-5] [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: 01/10/2023] [Revised: 10/02/2023] [Accepted: 10/23/2023] [Indexed: 11/30/2023]
Abstract
Posttraumatic stress disorder (PTSD) is associated with lower cortical thickness (CT) in prefrontal, cingulate, and insular cortices in diverse trauma-affected samples. However, some studies have failed to detect differences between PTSD patients and healthy controls or reported that PTSD is associated with greater CT. Using data-driven dimensionality reduction, we sought to conduct a well-powered study to identify vulnerable networks without regard to neuroanatomic boundaries. Moreover, this approach enabled us to avoid the excessive burden of multiple comparison correction that plagues vertex-wise methods. We derived structural covariance networks (SCNs) by applying non-negative matrix factorization (NMF) to CT data from 961 PTSD patients and 1124 trauma-exposed controls without PTSD. We used regression analyses to investigate associations between CT within SCNs and PTSD diagnosis (with and without accounting for the potential confounding effect of trauma type) and symptom severity in the full sample. We performed additional regression analyses in subsets of the data to examine associations between SCNs and comorbid depression, childhood trauma severity, and alcohol abuse. NMF identified 20 unbiased SCNs, which aligned closely with functionally defined brain networks. PTSD diagnosis was most strongly associated with diminished CT in SCNs that encompassed the bilateral superior frontal cortex, motor cortex, insular cortex, orbitofrontal cortex, medial occipital cortex, anterior cingulate cortex, and posterior cingulate cortex. CT in these networks was significantly negatively correlated with PTSD symptom severity. Collectively, these findings suggest that PTSD diagnosis is associated with widespread reductions in CT, particularly within prefrontal regulatory regions and broader emotion and sensory processing cortical regions.
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Affiliation(s)
- Jin Yang
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Ashley A Huggins
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
- Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA
| | - Delin Sun
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
- Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA
- Department of Psychology, The Education University of Hong Kong, Hong Kong, China
| | - C Lexi Baird
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
- Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA
| | - Courtney C Haswell
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA
- Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA
| | - Jessie L Frijling
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Miranda Olff
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands
- ARQ National Psychotrauma Centre, Diemen, The Netherlands
| | - Mirjam van Zuiden
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Saskia B J Koch
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Laura Nawijn
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Benjamin Suarez-Jimenez
- Del Monte Institute for Neuroscience, University of Rochester Medical Center, Rochester, NY, USA
| | - Xi Zhu
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Yuval Neria
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA
- New York State Psychiatric Institute, New York, NY, USA
| | - Anna R Hudson
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Sven C Mueller
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Justin T Baker
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Institute for Technology in Psychiatry, McLean Hospital, Harvard University, Belmont, MA, USA
| | - Lauren A M Lebois
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Division of Depression and Anxiety Disorders, McLean Hospital, Belmont, MA, USA
| | - Milissa L Kaufman
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Division of Women's Mental Health, McLean Hospital, Belmont, MA, USA
| | - Rongfeng Qi
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Jiangsu, China
| | - Guang Ming Lu
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Jiangsu, China
| | - Pavel Říha
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
- CEITEC-Central European Institute of Technology, Multimodal and Functional Neuroimaging Research Group, Masaryk University, Brno, Czech Republic
| | - Ivan Rektor
- CEITEC-Central European Institute of Technology, Multimodal and Functional Neuroimaging Research Group, Masaryk University, Brno, Czech Republic
| | - Emily L Dennis
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, 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
| | - Sophia I Thomopoulos
- 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
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - Dan J Stein
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Sheri M Koopowitz
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Jonathan C Ipser
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Soraya Seedat
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | - Stefan du Plessis
- Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | | | - 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
| | - 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
| | - Anika Sierk
- University Medical Centre Charité, Berlin, Germany
| | | | | | - Judith K Daniels
- Department of Clinical Psychology, University of Groningen, Groningen, The Netherlands
| | - Christian Schmahl
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Julia I Herzog
- Department of Psychosomatic Medicine and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Israel Liberzon
- Department of Psychiatry and Behavioral Science, Texas A&M University, College Station, TX, USA
| | - Anthony King
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Mike Angstadt
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas D Davenport
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Scott R Sponheim
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Seth G Disner
- Minneapolis VA Health Care System, Minneapolis, MN, USA
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - Thomas Straube
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
| | - David Hofmann
- Institute of Medical Psychology and Systems Neuroscience, University of Münster, Münster, Germany
| | - 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
| | - 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
| | - Terri A deRoon-Cassini
- Division of Trauma and Acute Care Surgery, Department of Surgery, Medical College of Wisconsin, Milwaukee, WI, USA
- Comprehensive Injury Center, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Jennifer U Blackford
- Munroe-Meyer Institute, University of Nebraska Medical Center, Omaha, NE, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bunmi O Olatunji
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | - Evan M Gordon
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, 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
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry of Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Ifat Levy
- Department of Comparative Medicine, Yale University, New Haven, CT, USA
- Department of Neuroscience, Yale University, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA
| | - Ilan Harpaz-Rotem
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA
| | - John H Krystal
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Division of Clinical Neuroscience, National Center for PTSD, West Haven, CT, USA
| | - Rajendra A Morey
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, NC, USA.
- Mid-Atlantic Mental Illness Research Education and Clinical Center, Durham VA Medical Center, Durham, NC, USA.
| | - Aristeidis Sotiras
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Institute for Informatics, Data Science & Biostatistics, Washington University in St. Louis, St. Louis, MO, USA
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Zhang R, Blair RJR, Blair KS, Dobbertin M, Elowsky J, Bashford-Largo J, Dominguez AJ, Hatch M, Bajaj S. Reduced grey matter volume in adolescents with conduct disorder: a region-of-interest analysis using multivariate generalized linear modeling. DISCOVER MENTAL HEALTH 2023; 3:25. [PMID: 37975932 PMCID: PMC10656392 DOI: 10.1007/s44192-023-00052-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 11/03/2023] [Indexed: 11/19/2023]
Abstract
BACKGROUND Conduct disorder (CD) involves a group of behavioral and emotional problems that usually begins during childhood or adolescence. Structural brain alterations have been observed in CD, including the amygdala, insula, ventrolateral and medial prefrontal cortex, anterior cingulate cortex, and fusiform gyrus. The current study developed a multivariate generalized linear model (GLM) to differentiate adolescents with CD from typically developing (TD) adolescents in terms of grey matter volume (GMV). METHODS The whole-brain structural MRI data were collected from 96 adolescents with CD (mean age = [Formula: see text] years; mean IQ = [Formula: see text]; 63 males) and 90 TD individuals (mean age = [Formula: see text] years; mean IQ = [Formula: see text]; 59 males) matched on age, IQ, and sex. Region-wise GMV was extracted following whole-brain parcellation into 68 cortical and 14 subcortical regions for each participant. A multivariate GLM was developed to predict the GMV of the pre-hypothesized regions-of-interest (ROIs) based on CD diagnosis, with intracranial volume, age, sex, and IQ serving as the covariate. RESULTS A diagnosis of CD was a significant predictor for GMV in the right pars orbitalis, right insula, right superior temporal gyrus, left fusiform gyrus, and left amygdala (F(1, 180) = 5.460-10.317, p < 0.05, partial eta squared = 0.029-0.054). The CD participants had smaller GMV in these regions than the TD participants (MCD-MTD = [- 614.898] mm3-[- 53.461] mm3). CONCLUSIONS Altered GMV within specific regions may serve as a biomarker for the development of CD in adolescents. Clinical work can potentially target these biomarkers to treat adolescents with CD.
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Affiliation(s)
- Ru Zhang
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA.
| | - R 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
| | - Matthew Dobbertin
- Inpatient Psychiatric Care Unit, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Jaimie Elowsky
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA
| | | | - Ahria J Dominguez
- Clinical Health, Emotion, and Neuroscience (CHEN) Laboratory, Department of Neurological Sciences, College of Medicine, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Melissa Hatch
- Mind and Brain Health Labs (MBHL), Department of Neurological Sciences, College of Medicine, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Sahil Bajaj
- Department of Cancer Systems Imaging, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
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6
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Zhang R, Blair RJR, Blair KS, Dobbertin M, Elowsky J, Bashford-Largo J, Dominguez AJ, Hatch M, Bajaj S. Reduced Grey Matter Volume in Adolescents with Conduct Disorder: A Region-of-Interest Analysis Using Multivariate Generalized Linear Modeling. RESEARCH SQUARE 2023:rs.3.rs-3425545. [PMID: 37961148 PMCID: PMC10635381 DOI: 10.21203/rs.3.rs-3425545/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Background Conduct disorder (CD) involves a group of behavioral and emotional problems that usually begins during childhood or adolescence. Structural brain alterations have been observed in CD, including the amygdala, insula, ventrolateral and medial prefrontal cortex, anterior cingulate cortex, and fusiform gyrus. The current study developed a multivariate generalized linear model (GLM) to differentiate adolescents with CD from typically developing (TD) adolescents in terms of grey matter volume (GMV). Methods The whole-brain structural MRI data were collected from 96 adolescents with CD (mean age = years; mean IQ = ; 63 males) and 90 TD individuals (mean age = years; mean IQ = ; 59 males) matched on age, IQ, and sex. Region-wise GMV was extracted following whole-brain parcellation into 68 cortical and 14 subcortical regions for each participant. A multivariate GLM was developed to predict the GMV of the pre-hypothesized regions-of-interest (ROIs) based on CD diagnosis, with intracranial volume, age, sex, and IQ serving as the covariate. Results A diagnosis of CD was a significant predictor for GMV in the right pars orbitalis, right insula, right superior temporal gyrus, left fusiform gyrus, and left amygdala (F(1, 180) = 5.460 - 10.317, p < 0.05, partial eta squared = 0.029 - 0.054). The CD participants had smaller GMV in these regions than the TD participants (MCD - MTD = [-614.898] mm3 - [-53.461] mm3). Conclusions Altered GMV within specific regions may serve as a biomarker for the development of CD in adolescents. Clinical work can potentially target these biomarkers to treat adolescents with CD.
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Affiliation(s)
- Ru Zhang
- University of Southern California
| | | | | | | | | | | | | | | | - Sahil Bajaj
- The University of Texas MD Anderson Cancer Center
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7
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Zhang F, Liu B, Shao Y, Tan Y, Niu Q, Wang X, Zhang H. Evaluation of the default mode network using nonnegative matrix factorization in patients with cognitive impairment induced by occupational aluminum exposure. Cereb Cortex 2023; 33:9815-9821. [PMID: 37415087 DOI: 10.1093/cercor/bhad246] [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: 05/22/2023] [Revised: 06/15/2023] [Accepted: 06/17/2023] [Indexed: 07/08/2023] Open
Abstract
Aluminum (Al) is an important environmental pathogenic factor for neurodegenerative diseases, especially mild cognitive impairment (MCI). The aim of this study was to evaluate the gray matter volume of structural covariance network alterations in patients with Al-induced MCI. Male subjects who had been exposed to Al for >10 years were included in the present study. The plasma Al concentration, Montreal cognitive assessment (MoCA) score, and verbal memory assessed by the Rey auditory verbal learning test (AVLT) score were collected from each participant. Nonnegative matrix factorization was used to identify the structural covariance network. The neural structural basis for patients with Al-induced MCI was investigated using correlation analysis and group comparison. Plasma Al concentration was inversely related to MoCA scores, particularly AVLT scores. In patients with Al-induced MCI, the gray matter volume of the default mode network (DMN) was considerably lower than that in controls. Positive correlations were discovered between the DMN and MoCA scores as well as between the DMN and AVLT scores. In sum, long-term occupational Al exposure has a negative impact on cognition, primarily by affecting delayed recognition. The reduced gray matter volume of the DMN may be the neural mechanism of Al-induced MCI.
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Affiliation(s)
- Feifei Zhang
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, P.R. China
- Department of Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, China
| | - Bo Liu
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, P.R. China
- Department of Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, China
- Department of College of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province 030001, China
| | - Yinbo Shao
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, P.R. China
- Department of College of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi Province 030001, China
| | - Yan Tan
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, P.R. China
- Department of Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, China
| | - Qiao Niu
- Department of Occupational Health, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi Province 030001, P.R. China
| | - Xiaochun Wang
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, P.R. China
- Department of Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, China
| | - Hui Zhang
- Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, P.R. China
- Department of Shanxi Key Laboratory of Intelligent Imaging and Nanomedicine, First Hospital of Shanxi Medical University, Taiyuan, Shanxi Province 030001, China
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8
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Jung K, Yoon J, Ahn Y, Kim S, Shim I, Ko H, Jung SH, Kim J, Kim H, Lee DJ, Cha S, Lee H, Kim B, Cho MY, Cho H, Kim DS, Kim J, Park WY, Park TH, O Connell KS, Andreassen OA, Myung W, Won HH. Leveraging genetic overlap between irritability and psychiatric disorders to identify genetic variants of major psychiatric disorders. Exp Mol Med 2023; 55:1193-1202. [PMID: 37258574 PMCID: PMC10317967 DOI: 10.1038/s12276-023-01005-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 02/07/2023] [Accepted: 03/13/2023] [Indexed: 06/02/2023] Open
Abstract
Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [n] of additional SNPs = 105), BD I (n = 54), MDD (n = 107), and irritability (n = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders.
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Affiliation(s)
- Kyeongmin Jung
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, South Korea
| | - Joohyun Yoon
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, South Korea
| | - Yeeun Ahn
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Soyeon Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Injeong Shim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Hyunwoong Ko
- Interdisciplinary Program in Cognitive Science, Seoul National University, Seoul, 08826, South Korea
- Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul National University College of Medicine, Seoul, 03080, South Korea
- Dental Research Institute, Seoul National University School of Dentistry, Seoul, 03080, South Korea
| | - Sang-Hyuk Jung
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Jaeyoung Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, South Korea
| | - Hyejin Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Dong June Lee
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Soojin Cha
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Hyewon Lee
- Department of Health Administration and Management, College of Medical Sciences, Soonchunhyang University, Asan, 31538, South Korea
| | - Beomsu Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Min Young Cho
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Hyunbin Cho
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Dan Say Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Jinho Kim
- Precision Medicine Center, Future Innovation Research Division, Seoul National University Bundang Hospital, Seongnam, 13620, South Korea
| | - Woong-Yang Park
- Samsung Genome Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, South Korea
| | - Tae Hwan Park
- Department of Plastic and Reconstructive Surgery, Hallym University Dongtan Sacred Heart Hospital, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, 18450, South Korea
| | - Kevin S O Connell
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, NO-316, Norway
| | - Ole A Andreassen
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, NO-316, Norway
| | - Woojae Myung
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, South Korea.
- Department of Psychiatry, Seoul National University, College of Medicine, Seoul, 03080, South Korea.
| | - Hong-Hee Won
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea.
- Samsung Genome Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, South Korea.
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9
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Albaugh MD, Hudziak JJ, Spechler PA, Chaarani B, Lepage C, Jeon S, Rioux P, Evans AC, Banaschewski T, Bokde ALW, Desrivières S, Flor H, Gowland P, Heinz A, Ittermann B, Martinot JL, Martinot MLP, Nees F, Orfanos DP, Poustka L, Millenet S, Fröhner JH, Smolka MN, Walter H, Whelan R, Schumann G, Potter AS, Garavan H. Conduct problems are associated with accelerated thinning of emotion-related cortical regions in a community-based sample of adolescents. Psychiatry Res Neuroimaging 2023; 330:111614. [PMID: 36812809 DOI: 10.1016/j.pscychresns.2023.111614] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 02/13/2023] [Indexed: 02/17/2023]
Abstract
Few studies have examined the association between conduct problems and cerebral cortical development. Herein, we characterize the association between age-related brain change and conduct problems in a large longitudinal, community-based sample of adolescents. 1,039 participants from the IMAGEN study possessed psychopathology and surface-based morphometric data at study baseline (M = 14.42 years, SD = 0.40; 559 females) and 5-year follow-up. Self-reports of conduct problems were obtained using the Strengths and Difficulties Questionnaire (SDQ). Vertex-level linear mixed effects models were implemented using the Matlab toolbox, SurfStat. To investigate the extent to which cortical thickness maturation was qualified by dimensional measures of conduct problems, we tested for an interaction between age and SDQ Conduct Problems (CP) score. There was no main effect of CP score on cortical thickness; however, a significant "Age by CP" interaction was revealed in bilateral insulae, left inferior frontal gyrus, left rostral anterior cingulate, left posterior cingulate, and bilateral inferior parietal cortices. Across regions, follow-up analysis revealed higher levels of CP were associated with accelerated age-related thinning. Findings were not meaningfully altered when controlling for alcohol use, co-occurring psychopathology, and socioeconomic status. Results may help to further elucidate neurodevelopmental patterns linking adolescent conduct problems with adverse adult outcomes.
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Affiliation(s)
- Matthew D Albaugh
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States of America.
| | - James J Hudziak
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States of America
| | - Philip A Spechler
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States of America
| | - Bader Chaarani
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States of America
| | - Claude Lepage
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Seun Jeon
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Pierre Rioux
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Alan C Evans
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, United Kingdom
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany; Department of Psychology, School of Social Sciences, University of Mannheim, 68131 Mannheim, Germany
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany [or depending on journal requirements can be: Physikalisch-Technische Bundesanstalt (PTB), Abbestr. 2 - 12, Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 "Trajectoires développementales & psychiatrie", University Paris-Saclay, CNRS, Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 "Trajectoires développementales & psychiatrieȝ, University Paris-Saclay, CNRS; Ecole Normale Supérieure Paris-Saclay, Centre Borelli; Gif-sur-Yvette, Paris; France; AP-HP. Sorbonne University, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris; France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany; Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | | | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Germany; Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Alexandra S Potter
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States of America
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, United States of America
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10
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Xia CH, Barnett I, Tapera TM, Adebimpe A, Baker JT, Bassett DS, Brotman MA, Calkins ME, Cui Z, Leibenluft E, Linguiti S, Lydon-Staley DM, Martin ML, Moore TM, Murtha K, Piiwaa K, Pines A, Roalf DR, Rush-Goebel S, Wolf DH, Ungar LH, Satterthwaite TD. Mobile footprinting: linking individual distinctiveness in mobility patterns to mood, sleep, and brain functional connectivity. Neuropsychopharmacology 2022; 47:1662-1671. [PMID: 35660803 PMCID: PMC9163291 DOI: 10.1038/s41386-022-01351-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 05/18/2022] [Accepted: 05/23/2022] [Indexed: 11/09/2022]
Abstract
Mapping individual differences in behavior is fundamental to personalized neuroscience, but quantifying complex behavior in real world settings remains a challenge. While mobility patterns captured by smartphones have increasingly been linked to a range of psychiatric symptoms, existing research has not specifically examined whether individuals have person-specific mobility patterns. We collected over 3000 days of mobility data from a sample of 41 adolescents and young adults (age 17-30 years, 28 female) with affective instability. We extracted summary mobility metrics from GPS and accelerometer data and used their covariance structures to identify individuals and calculated the individual identification accuracy-i.e., their "footprint distinctiveness". We found that statistical patterns of smartphone-based mobility features represented unique "footprints" that allow individual identification (p < 0.001). Critically, mobility footprints exhibited varying levels of person-specific distinctiveness (4-99%), which was associated with age and sex. Furthermore, reduced individual footprint distinctiveness was associated with instability in affect (p < 0.05) and circadian patterns (p < 0.05) as measured by environmental momentary assessment. Finally, brain functional connectivity, especially those in the somatomotor network, was linked to individual differences in mobility patterns (p < 0.05). Together, these results suggest that real-world mobility patterns may provide individual-specific signatures relevant for studies of development, sleep, and psychopathology.
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Affiliation(s)
- Cedric Huchuan Xia
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ian Barnett
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Tinashe M Tapera
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Azeez Adebimpe
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Justin T Baker
- McLean Institute for Technology in Psychiatry, McLean Hospital, Belmont, MA, 02478, USA.,Department of Psychiatry, Harvard Medical School, Boston, MA, 02115, USA
| | - Danielle S Bassett
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Santa Fe Institute, Santa Fe, NM, 87501, USA
| | - Melissa A Brotman
- National Institute of Mental Health, Intramural Research Program, Bethesda, MD, 20892, USA
| | - Monica E Calkins
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Zaixu Cui
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ellen Leibenluft
- National Institute of Mental Health, Intramural Research Program, Bethesda, MD, 20892, USA
| | - Sophia Linguiti
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - David M Lydon-Staley
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Annenberg School of Communication, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Leonard Davis Institute for Health Economics, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Melissa Lynne Martin
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Tyler M Moore
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Kristin Murtha
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Kayla Piiwaa
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Adam Pines
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - David R Roalf
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sage Rush-Goebel
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Daniel H Wolf
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Lyle H Ungar
- Department of Computer and Information Science, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Department of Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.,Department of Operations, Information and Decisions, Wharton School, Philadelphia, PA, 19104, USA.,Department of Psychology, School of Arts and Sciences, Philadelphia, PA, 19104, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA. .,Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA. .,Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA, 19104, USA. .,Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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11
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Damme KSF, Norton ES, Briggs-Gowan MJ, Wakschlag LS, Mittal VA. Developmental patterning of irritability enhances prediction of psychopathology in preadolescence: Improving RDoC with developmental science. JOURNAL OF PSYCHOPATHOLOGY AND CLINICAL SCIENCE 2022; 131:556-566. [PMID: 35901387 PMCID: PMC9439570 DOI: 10.1037/abn0000655] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
The transdiagnostic importance of irritability in psychopathology has been demonstrated. However, the contribution of developmentally unfolding irritability patterns to specific clinical and neural outcomes remains an important and unanswered question. To address this gap in the literature, irritability patterns of 110 youth from a large, diverse cohort were assessed at preschool age and again at early school age (∼2.5 years later) with a dimensional irritability scale designed to capture the normal:abnormal spectrum. At preadolescence (∼6 years later), clinical outcomes (internalizing/externalizing symptoms) derived from a semistructured clinical interview and neural outcomes (characterized as gray-matter-volume abnormalities) were assessed. For clinical outcomes, preschool-age irritability alone was a transdiagnostic predictor of internalizing and externalizing symptoms at preadolescence. However, in a model including both preschool and early school age, irritability provided greater specificity, suggesting that higher irritability at early school age related to elevated preadolescent externalizing but not internalizing symptoms. In terms of neural outcomes, elevated preschool irritability did not predict preadolescent gray-matter-volume abnormality; however, irritability at early school age demonstrated an interactive effect among regions, with reduced volume in preadolescence emotional regions (e.g., amygdala, medial orbitofrontal cortex) and increased volume in other regions (e.g., cerebellum). These complex patterns highlight the contribution of a developmentally informed approach, the National Institute of Mental Health's Research Domain Criteria (RDoC) approach, to yield transdiagnostic phenotypes and multiple units of analysis. Capturing these individual differences and developmental heterogeneity can provide critical insight into the unfolding of mechanisms underlying emerging psychopathology. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Affiliation(s)
| | - Elizabeth S Norton
- Department of Communication Sciences and Disorders, Northwestern University
| | | | - Lauren S Wakschlag
- Institute for Innovations in Developmental Sciences (DevSci), Northwestern University
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12
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Ottino-González J, Garavan H. Brain structural covariance network differences in adults with alcohol dependence and heavy-drinking adolescents. Addiction 2022; 117:1312-1325. [PMID: 34907616 DOI: 10.1111/add.15772] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 11/05/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND AND AIMS Graph theoretic analysis of structural covariance networks (SCN) provides an assessment of brain organization that has not yet been applied to alcohol dependence (AD). We estimated whether SCN differences are present in adults with AD and heavy-drinking adolescents at age 19 and age 14, prior to substantial exposure to alcohol. DESIGN Cross-sectional sample of adults and a cohort of adolescents. Correlation matrices for cortical thicknesses across 68 regions were summarized with graph theoretic metrics. SETTING AND PARTICIPANTS A total of 745 adults with AD and 979 non-dependent controls from 24 sites curated by the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA)-Addiction consortium, and 297 hazardous drinking adolescents and 594 controls at ages 19 and 14 from the IMAGEN study, all from Europe. MEASUREMENTS Metrics of network segregation (modularity, clustering coefficient and local efficiency) and integration (average shortest path length and global efficiency). FINDINGS The younger AD adults had lower network segregation and higher integration relative to non-dependent controls. Compared with controls, the hazardous drinkers at age 19 showed lower modularity [area-under-the-curve (AUC) difference = -0.0142, 95% confidence interval (CI) = -0.1333, 0.0092; P-value = 0.017], clustering coefficient (AUC difference = -0.0164, 95% CI = -0.1456, 0.0043; P-value = 0.008) and local efficiency (AUC difference = -0.0141, 95% CI = -0.0097, 0.0034; P-value = 0.010), as well as lower average shortest path length (AUC difference = -0.0405, 95% CI = -0.0392, 0.0096; P-value = 0.021) and higher global efficiency (AUC difference = 0.0044, 95% CI = -0.0011, 0.0043; P-value = 0.023). The same pattern was present at age 14 with lower clustering coefficient (AUC difference = -0.0131, 95% CI = -0.1304, 0.0033; P-value = 0.024), lower average shortest path length (AUC difference = -0.0362, 95% CI = -0.0334, 0.0118; P-value = 0.019) and higher global efficiency (AUC difference = 0.0035, 95% CI = -0.0011, 0.0038; P-value = 0.048). CONCLUSIONS Cross-sectional analyses indicate that a specific structural covariance network profile is an early marker of alcohol dependence in adults. Similar effects in a cohort of heavy-drinking adolescents, observed at age 19 and prior to substantial alcohol exposure at age 14, suggest that this pattern may be a pre-existing risk factor for problematic drinking.
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Affiliation(s)
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
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13
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Hirjak D, Henemann GM, Schmitgen MM, Götz L, Wolf ND, Kubera KM, Sambataro F, Leménager T, Koenig J, Wolf RC. Cortical surface variation in individuals with excessive smartphone use. Dev Neurobiol 2022; 82:277-287. [PMID: 35332986 DOI: 10.1002/dneu.22872] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 01/14/2022] [Accepted: 03/09/2022] [Indexed: 11/09/2022]
Abstract
Excessive smartphone use has been repeatedly related to adverse effects on mental health and psychological well-being in young adults. The continued investigation of the neurobiological mechanism underlying excessive smartphone use - sometimes also referred to as "smartphone addiction" (SPA) - is considered a top priority in system neuroscience research. Despite progress in the past years, cortical morphology associated with SPA is still poorly understood. Here, we used structural magnetic resonance imaging (MRI) at 3 T to investigate two cortical surface markers of distinct neurodevelopmental origin such as the complexity of cortical folding (CCF) and cortical thickness (CTh) in individuals with excessive smartphone use (n = 19) compared to individuals not fulfilling SPA criteria (n-SPA; n = 22). SPA was assessed using the Smartphone Addiction Inventory (SPAI). CCF and CTh were investigated using the Computational Anatomy Toolbox (CAT12). SPA individuals showed lower CCF in the right superior frontal gyrus as well as in the right caudal (cACC) and rostral anterior cingulate cortex (rACC) compared to n-SPA individuals (TFCE, uncorrected at p < 0.001). Following a dimensional approach, across the entire sample CCF of the right cACC was significantly associated with SPAI total score, as well as with distinct SPAI subdimensions, particularly time spent with the device, compulsivity, and sleep interference in all participants (n = 41; p < 0.05, FDR-corrected). Collectively, these findings suggest that SPA is associated with aberrant structural maturation of regions important for cognitive control and emotional regulation. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Gudrun M Henemann
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Mike M Schmitgen
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Larissa Götz
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Nadine D Wolf
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Katharina M Kubera
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
| | - Fabio Sambataro
- Department of Neurosciences, Padua Neuroscience Center, University of Padova, Padua, Italy
| | - Tagrid Leménager
- Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Julian Koenig
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Cologne, Germany
| | - Robert Christian Wolf
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Heidelberg, Germany
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14
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Network-wise surface-based morphometric insight into the cortical neural circuitry underlying irritability in adolescents. Transl Psychiatry 2021; 11:581. [PMID: 34759268 PMCID: PMC8581009 DOI: 10.1038/s41398-021-01710-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 10/18/2021] [Accepted: 10/25/2021] [Indexed: 11/08/2022] Open
Abstract
Previous studies examining structural brain correlates of irritability have taken a region-specific approach and have been relatively inconsistent. In a sample of adolescents with and without clinically impairing irritability, the current study examines: (i) cortical volume (CV) in canonical functional networks; (ii) the association between the CV of functional networks and severity of irritability; and (iii) the extent to which IQ mediates the association between structural abnormalities and severity of irritability. Structural MRI and IQ data were collected from 130 adolescents with high irritability (mean age = 15.54±1.83 years, 58 females, self-reported Affective Reactivity Index [ARI] ≥ 4) and 119 adolescents with low irritability (mean age = 15.10±1.93 years, 39 females, self-reported ARI < 4). Subject-specific network-wise CV was estimated after parcellating the whole brain into 17 previously reported functional networks. Our Multivariate Analysis of Covariance (MANCOVA) revealed that adolescents with high irritability had significantly reduced CV of the bilateral control and default-mode networks (p < 0.05) relative to adolescents with low irritability. Multiple regression analyses showed a significant negative association between the control network CV and the severity of irritability. Mediation analysis showed that IQ partially mediated the association between the control network CV and the severity of irritability. Follow-up analysis on subcortical volume (SCV) showed that adolescents with high irritability had reduced bilateral SCV within the amygdala relative to adolescents with low irritability. Reduced CV within bilateral control and default networks and reduced SCV within bilateral amygdala may represent core features of the pathophysiology of irritability. The current data also indicate the potential importance of a patient's IQ in determining how pathophysiology related to the control network is expressed.
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15
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Lucey BP, Wisch J, Boerwinkle AH, Landsness EC, Toedebusch CD, McLeland JS, Butt OH, Hassenstab J, Morris JC, Ances BM, Holtzman DM. Sleep and longitudinal cognitive performance in preclinical and early symptomatic Alzheimer's disease. Brain 2021; 144:2852-2862. [PMID: 34668959 PMCID: PMC8536939 DOI: 10.1093/brain/awab272] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 06/13/2021] [Accepted: 07/01/2021] [Indexed: 11/12/2022] Open
Abstract
Sleep monitoring may provide markers for future Alzheimer's disease; however, the relationship between sleep and cognitive function in preclinical and early symptomatic Alzheimer's disease is not well understood. Multiple studies have associated short and long sleep times with future cognitive impairment. Since sleep and the risk of Alzheimer's disease change with age, a greater understanding of how the relationship between sleep and cognition changes over time is needed. In this study, we hypothesized that longitudinal changes in cognitive function will have a non-linear relationship with total sleep time, time spent in non-REM and REM sleep, sleep efficiency and non-REM slow wave activity. To test this hypothesis, we monitored sleep-wake activity over 4-6 nights in 100 participants who underwent standardized cognitive testing longitudinally, APOE genotyping, and measurement of Alzheimer's disease biomarkers, total tau and amyloid-β42 in the CSF. To assess cognitive function, individuals completed a neuropsychological testing battery at each clinical visit that included the Free and Cued Selective Reminding test, the Logical Memory Delayed Recall assessment, the Digit Symbol Substitution test and the Mini-Mental State Examination. Performance on each of these four tests was Z-scored within the cohort and averaged to calculate a preclinical Alzheimer cognitive composite score. We estimated the effect of cross-sectional sleep parameters on longitudinal cognitive performance using generalized additive mixed effects models. Generalized additive models allow for non-parametric and non-linear model fitting and are simply generalized linear mixed effects models; however, the linear predictors are not constant values but rather a sum of spline fits. We found that longitudinal changes in cognitive function measured by the cognitive composite decreased at low and high values of total sleep time (P < 0.001), time in non-REM (P < 0.001) and REM sleep (P < 0.001), sleep efficiency (P < 0.01) and <1 Hz and 1-4.5 Hz non-REM slow wave activity (P < 0.001) even after adjusting for age, CSF total tau/amyloid-β42 ratio, APOE ε4 carrier status, years of education and sex. Cognitive function was stable over time within a middle range of total sleep time, time in non-REM and REM sleep and <1 Hz slow wave activity, suggesting that certain levels of sleep are important for maintaining cognitive function. Although longitudinal and interventional studies are needed, diagnosing and treating sleep disturbances to optimize sleep time and slow wave activity may have a stabilizing effect on cognition in preclinical or early symptomatic Alzheimer's disease.
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Affiliation(s)
- Brendan P Lucey
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Julie Wisch
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Anna H Boerwinkle
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Eric C Landsness
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Cristina D Toedebusch
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Jennifer S McLeland
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Omar H Butt
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Beau M Ances
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO 63110, USA
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
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16
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Nielsen AN, Wakschlag LS, Norton ES. Linking irritability and functional brain networks: A transdiagnostic case for expanding consideration of development and environment in RDoC. Neurosci Biobehav Rev 2021; 129:231-244. [PMID: 34302863 PMCID: PMC8802626 DOI: 10.1016/j.neubiorev.2021.07.022] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 07/14/2021] [Accepted: 07/17/2021] [Indexed: 01/13/2023]
Abstract
The National Institute of Mental Health Research Domain Criteria (RDoC) framework promotes the dimensional and transdiagnostic operationalization of psychopathology, but consideration of the neurodevelopmental foundations of mental health problems requires deeper examination. Irritability, the dispositional tendency to angry emotion that has both mood and behavioral elements, is dimensional, transdiagnostic, and observable early in life-a promising target for the identification of early neural indicators or risk factors for psychopathology. Here, we examine functional brain networks linked to irritability from preschool to adulthood and discuss how development and early experience may influence these neural substrates. Functional connectivity measured with fMRI varies according to irritability and indicates the atypical coordination of several functional networks involved in emotion generation, emotion perception, attention, internalization, and cognitive control. We lay out an agenda to improve our understanding and detection of atypical brain:behavior patterns through advances in the characterization of both functional networks and irritability as well as the consideration and operationalization of developmental and early life environmental influences on this pathway.
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Affiliation(s)
- Ashely N Nielsen
- Department of Medical Social Sciences, Northwestern University, Chicago, IL, United States; Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL, United States.
| | - Lauren S Wakschlag
- Department of Medical Social Sciences, Northwestern University, Chicago, IL, United States; Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL, United States
| | - Elizabeth S Norton
- Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL, United States; Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL, United States
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17
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Neural correlates of irritability in a community sample of children. J Affect Disord 2021; 292:223-226. [PMID: 34130187 DOI: 10.1016/j.jad.2021.05.093] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 04/20/2021] [Accepted: 05/31/2021] [Indexed: 11/21/2022]
Abstract
Irritability has been associated with aberrant patterns of neural activation, yet little is known about structural brain correlates of irritability. As such, we aimed to investigate associations between irritability and gray matter volume (GMV) in a community sample of children enriched for irritability. The sample comprised children (n=162) aged 9-11 years with and without Attention-Deficit/Hyperactivity Disorder (ADHD), participating in a cohort study with magnetic resonance imaging data available. Mixed effects linear regression analyses tested the associations between irritability symptoms and regional GMV (extracted using Freesurfer). Irritability was associated with smaller gray matter volume across multiple brain regions implicated in executive functioning, and emotion and reward processing including frontal regions and the cingulate.
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18
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Seok JW, Bajaj S, Soltis-Vaughan B, Lerdahl A, Garvey W, Bohn A, Edwards R, Kratochvil CJ, Blair J, Hwang S. Structural atrophy of the right superior frontal gyrus in adolescents with severe irritability. Hum Brain Mapp 2021; 42:4611-4622. [PMID: 34288223 PMCID: PMC8410540 DOI: 10.1002/hbm.25571] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Revised: 05/22/2021] [Accepted: 06/10/2021] [Indexed: 12/27/2022] Open
Abstract
Severe irritability is common in youths with psychiatric disorders and results in significant dysfunction across domains (academic, social, and familial). Prior structural MRI studies in the pediatric population demonstrated that aberrations of cortical thickness (CT) and gray matter volume (GMV) in the fronto‐striatal‐temporal regions which have been associated with irritability. However, the directions of the correlations between structural alteration and irritability in the individual indices were not consistent. Thus, we aim to address this by implementing comprehensive assessments of CT, GMV, and local gyrification index (LGI) simultaneously in youths with severe levels of irritability by voxel‐based morphometry and surface‐based morphometry. One hundred and eight adolescents (46 youths with severe irritability and 62 healthy youths, average age = 14.08 years, standard deviation = 2.36) were scanned with a T1‐weighted MRI sequence. The severity of irritability was measured using the affective reactivity index. In youths with severe irritability, there was decreased CT, GMV, and LGI in the right superior frontal gyrus (SFG) compared to healthy youths, and negative correlations between these indices of the SFG and irritability. Our findings suggest that structural deficits in the SFG, potentially related to its role in inhibitory control, may be critical for the neurobiology of irritability.
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Affiliation(s)
- Ji-Woo Seok
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Sahil Bajaj
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | | | - Arica Lerdahl
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - William Garvey
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Alexandra Bohn
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | - Ryan Edwards
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, Nebraska, USA
| | | | - James Blair
- Center for Neurobehavioral Research, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | - Soonjo Hwang
- Department of Psychiatry, University of Nebraska Medical Center, Omaha, Nebraska, USA
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19
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Nadig A, Seidlitz J, McDermott CL, Liu S, Bethlehem R, Moore TM, Mallard TT, Clasen LS, Blumenthal JD, Lalonde F, Gur RC, Gur RE, Bullmore ET, Satterthwaite TD, Raznahan A. Morphological integration of the human brain across adolescence and adulthood. Proc Natl Acad Sci U S A 2021; 118:e2023860118. [PMID: 33811142 PMCID: PMC8040585 DOI: 10.1073/pnas.2023860118] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
Brain structural covariance norms capture the coordination of neurodevelopmental programs between different brain regions. We develop and apply anatomical imbalance mapping (AIM), a method to measure and model individual deviations from these norms, to provide a lifespan map of morphological integration in the human cortex. In cross-sectional and longitudinal data, analysis of whole-brain average anatomical imbalance reveals a reproducible tightening of structural covariance by age 25 y, which loosens after the seventh decade of life. Anatomical imbalance change in development and in aging is greatest in the association cortex and least in the sensorimotor cortex. Finally, we show that interindividual variation in whole-brain average anatomical imbalance is positively correlated with a marker of human prenatal stress (birthweight disparity between monozygotic twins) and negatively correlated with general cognitive ability. This work provides methods and empirical insights to advance our understanding of coordinated anatomical organization of the human brain and its interindividual variation.
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Affiliation(s)
- Ajay Nadig
- Harvard/MIT MD-PhD Program, Harvard Medical School, Boston, MA, 02115;
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD, 20892
| | - Jakob Seidlitz
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD, 20892
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104
| | - Cassidy L McDermott
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD, 20892
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, 19104
| | - Siyuan Liu
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD, 20892
| | - Richard Bethlehem
- Department of Psychiatry, University of Cambridge, Cambridge CB2 1TN, United Kingdom
| | - Tyler M Moore
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104
| | - Travis T Mallard
- Department of Psychology, University of Texas at Austin, Austin, TX, 78712
| | - Liv S Clasen
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD, 20892
| | - Jonathan D Blumenthal
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD, 20892
| | - François Lalonde
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD, 20892
| | - Ruben C Gur
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104
| | - Raquel E Gur
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, 19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104
| | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge CB2 1TN, United Kingdom
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge CB2 1TN, United Kingdom
| | | | - Armin Raznahan
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD, 20892
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20
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Piguet C, Mihailov A, Grigis A, Laidi C, Duchesnay E, Houenou J. Irritability Is Associated With Decreased Cortical Surface Area and Anxiety With Decreased Gyrification During Brain Development. Front Psychiatry 2021; 12:744419. [PMID: 34630188 PMCID: PMC8492928 DOI: 10.3389/fpsyt.2021.744419] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 08/25/2021] [Indexed: 11/14/2022] Open
Abstract
Background: Brain development is of utmost importance for the emergence of psychiatric disorders, as the most severe of them arise before 25 years old. However, little is known regarding how early transdiagnostic symptoms, in a dimensional framework, are associated with cortical development. Anxiety and irritability are central vulnerability traits for subsequent mood and anxiety disorders. In this study, we investigate how these dimensions are related to structural changes in the brain to understand how they may increase the transition risk to full-blown disorders. Methods: We used the opportunity of an open access developmental cohort, the Healthy Brain Network, to investigate associations between cortical surface markers and irritability and anxiety scores as measured by parents and self-reports. Results: We found that in 658 young people (with a mean age of 11.6) the parental report of irritability is associated with decreased surface area in the bilateral rostral prefrontal cortex and the precuneus. Furthermore, parental reports of anxiety were associated with decreased local gyrification index in the anterior cingulate cortex and dorsomedial prefrontal cortex. Conclusions: These results are consistent with current models of emotion regulation network maturation, showing decreased surface area or gyrification index in regions associated with impaired affective control in mood and anxiety disorders. Our results highlight how dimensional traits may increase vulnerability for these disorders.
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Affiliation(s)
- Camille Piguet
- NeuroSpin, CEA, University Paris Saclay, Gif-sur-Yvette, France.,Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | | | - Antoine Grigis
- NeuroSpin, CEA, University Paris Saclay, Gif-sur-Yvette, France
| | - Charles Laidi
- NeuroSpin, CEA, University Paris Saclay, Gif-sur-Yvette, France.,Université Paris Est Créteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France.,Assistance Publique-Hôpitaux de Paris (AP-HP), DMU IMPACT, Mondor University Hospitals, Créteil, France
| | | | - Josselin Houenou
- NeuroSpin, CEA, University Paris Saclay, Gif-sur-Yvette, France.,Université Paris Est Créteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France.,Assistance Publique-Hôpitaux de Paris (AP-HP), DMU IMPACT, Mondor University Hospitals, Créteil, France
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21
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Chad-Friedman E, Botdorf M, Riggins T, Dougherty LR. Parental hostility predicts reduced cortical thickness in males. Dev Sci 2020; 24:e13052. [PMID: 33091205 DOI: 10.1111/desc.13052] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 09/23/2020] [Accepted: 10/13/2020] [Indexed: 01/22/2023]
Abstract
Although impacts of negative parenting on children's brain development are well-documented, little is known about how these associations may differ for males and females in childhood. We examined interactions between child sex and early and concurrent parental hostility on children's cortical thickness and surface area. Participants included 63 children (50.8% female) assessed during early childhood (Wave 1: M age = 4.23 years, SD = 0.84) and again three years later (Wave 2: M age = 7.19 years, SD = 0.89) using an observational parent-child interaction task. At Wave 2, children completed a structural MRI scan. Analyses focused on regions of interest. After correcting for multiple comparisons, Wave 1 parental hostility predicted males' reduced thickness in middle frontal and fusiform cortices, and Wave 2 parental hostility was concurrently associated with males' reduced thickness in the middle frontal cortex. Interactions between sex and parenting on children's surface area did not survive corrections for multiple comparisons. Our findings provide support for a male-specific neural vulnerability of hostile parenting across development. Results have important implications for uncovering neural pathways to sex-differences in psychopathology, learning, and cognitive disabilities.
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Affiliation(s)
| | - Morgan Botdorf
- University of Maryland College Park, College Park, MD, USA
| | - Tracy Riggins
- University of Maryland College Park, College Park, MD, USA
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22
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Gender-Related and Hemispheric Effects in Cortical Thickness-Based Hemispheric Brain Morphological Network. BIOMED RESEARCH INTERNATIONAL 2020; 2020:3560259. [PMID: 32851064 PMCID: PMC7439209 DOI: 10.1155/2020/3560259] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 06/19/2020] [Accepted: 07/06/2020] [Indexed: 12/18/2022]
Abstract
Objective The current study examined gender-related differences in hemispheric asymmetries of graph metrics, calculated from a cortical thickness-based brain structural covariance network named hemispheric morphological network. Methods Using the T1-weighted magnetic resonance imaging scans of 285 participants (150 females, 135 males) retrieved from the Human Connectome Project (HCP), hemispheric morphological networks were constructed per participant. In these hemispheric morphologic networks, the degree of similarity between two different brain regions in terms of the distributed patterns of cortical thickness values (the Jensen–Shannon divergence) was defined as weight of network edge that connects two different brain regions. After the calculation and summation of global and local graph metrics (across the network sparsity levels K = 0.10‐0.36), asymmetry indexes of these graph metrics were derived. Results Hemispheric morphological networks satisfied small-worldness and global efficiency for the network sparsity ranges of K = 0.10–0.36. Between-group comparisons (female versus male) of asymmetry indexes revealed opposite directionality of asymmetries (leftward versus rightward) for global metrics of normalized clustering coefficient, normalized characteristic path length, and global efficiency (all p < 0.05). For the local graph metrics, larger rightward asymmetries of cingulate-superior parietal gyri for nodal efficiency in male compared to female, larger leftward asymmetry of temporal pole for degree centrality in female compared to male, and opposite directionality of interhemispheric asymmetry of rectal gyrus for degree centrality between female (rightward) and male (leftward) were shown (all p < 0.05). Conclusion Patterns of interhemispheric asymmetries for cingulate, superior parietal gyrus, temporal pole, and rectal gyrus are different between male and female for the similarities of the cortical thickness distribution with other brain regions. Accordingly, possible effect of gender-by-hemispheric interaction has to be considered in future studies of brain morphology and brain structural covariance networks.
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23
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Structural brain networks in remitted psychotic depression. Neuropsychopharmacology 2020; 45:1223-1231. [PMID: 32109935 PMCID: PMC7235256 DOI: 10.1038/s41386-020-0646-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Accepted: 02/18/2020] [Indexed: 12/12/2022]
Abstract
Major depressive disorder with psychotic features (psychotic depression) is a severe disorder. Compared with other psychotic disorders such as schizophrenia, relatively few studies on the neurobiology of psychotic depression have been pursued. Neuroimaging studies investigating psychotic depression have provided evidence for distributed structural brain abnormalities implicating the insular cortex and limbic system. We examined structural brain networks in participants (N = 245) using magnetic resonance imaging. This sample included healthy controls (n = 159) and the largest cross-sectional sample of patients with remitted psychotic depression (n = 86) collected to date. All patients participated in the Study of Pharmacotherapy of Psychotic Depression II randomized controlled trial. We used a novel, whole-brain, data-driven parcellation technique-non-negative matrix factorization-and applied it to cortical thickness data to derive structural covariance networks. We compared patients with remitted psychotic depression to healthy controls and found that patients had significantly thinner cortex in five structural covariance networks (insular-limbic, occipito-temporal, temporal, parahippocampal-limbic, and inferior fronto-temporal), confirming our hypothesis that affected brain networks would incorporate cortico-limbic regions. We also found that cross-sectional depression and severity scores at the time of scanning were associated with the insular-limbic network. Furthermore, the insular-limbic network predicted future severity scores that were collected at the time of recurrence of psychotic depression or sustained remission. Overall, decreased cortical thickness was found in five structural brain networks in patients with remitted psychotic depression and brain-behavior relationships were observed, particularly between the insular-limbic network and illness severity.
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24
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Longitudinal Development of Brain Iron Is Linked to Cognition in Youth. J Neurosci 2020; 40:1810-1818. [PMID: 31988059 DOI: 10.1523/jneurosci.2434-19.2020] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 12/19/2019] [Accepted: 01/04/2020] [Indexed: 11/21/2022] Open
Abstract
Brain iron is vital to multiple aspects of brain function, including oxidative metabolism, myelination, and neurotransmitter synthesis. Atypical iron concentration in the basal ganglia is associated with neurodegenerative disorders in aging and cognitive deficits. However, the normative development of brain iron concentration in adolescence and its relationship to cognition are less well understood. Here, we address this gap in a longitudinal sample of 922 humans aged 8-26 years at the first visit (M = 15.1, SD = 3.72; 336 males, 486 females) with up to four multiecho T2* scans each. Using this sample of 1236 imaging sessions, we assessed the longitudinal developmental trajectories of tissue iron in the basal ganglia. We quantified tissue iron concentration using R2* relaxometry within four basal ganglia regions, including the caudate, putamen, nucleus accumbens, and globus pallidus. The longitudinal development of R2* was modeled using generalized additive mixed models (GAMMs) with splines to capture linear and nonlinear developmental processes. We observed significant increases in R2* across all regions, with the greatest and most prolonged increases occurring in the globus pallidus and putamen. Further, we found that the developmental trajectory of R2* in the putamen is significantly related to individual differences in cognitive ability, such that greater cognitive ability is increasingly associated with greater iron concentration through late adolescence and young-adulthood. Together, our results suggest a prolonged period of basal ganglia iron enrichment that extends into the mid-twenties, with diminished iron concentration associated with poorer cognitive ability during late adolescence.SIGNIFICANCE STATEMENT Brain tissue iron is essential to healthy brain function. Atypical basal ganglia tissue iron levels have been linked to impaired cognition in iron deficient children and adults with neurodegenerative disorders. However, the normative developmental trajectory of basal ganglia iron concentration during adolescence and its association with cognition are less well understood. In the largest study of tissue iron development yet reported, we characterize the developmental trajectory of tissue iron concentration across the basal ganglia during adolescence and provide evidence that diminished iron content is associated with poorer cognitive performance even in healthy youth. These results highlight the transition from adolescence to adulthood as a period of dynamic maturation of tissue iron concentration in the basal ganglia.
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Ferschmann L, Vijayakumar N, Grydeland H, Overbye K, Sederevicius D, Due-Tønnessen P, Fjell AM, Walhovd KB, Pfeifer JH, Tamnes CK. Prosocial behavior relates to the rate and timing of cortical thinning from adolescence to young adulthood. Dev Cogn Neurosci 2019; 40:100734. [PMID: 31739096 PMCID: PMC6974908 DOI: 10.1016/j.dcn.2019.100734] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Revised: 10/21/2019] [Accepted: 11/04/2019] [Indexed: 12/21/2022] Open
Abstract
Prosocial behavior, or voluntary actions that intentionally benefit others, relate to desirable developmental outcomes such as peer acceptance, while lack of prosocial behavior has been associated with several neurodevelopmental disorders. Mapping the biological foundations of prosociality may thus aid our understanding of both normal and abnormal development, yet how prosociality relates to cortical development is largely unknown. Here, relations between prosociality, as measured by the Strengths and Difficulties Questionnaire (self-report), and changes in thickness across the cortical mantle were examined using mixed-effects models. The sample consisted of 169 healthy individuals (92 females) aged 12-26 with repeated MRI from up to 3 time points, at approximately 3-year intervals (301 scans). In regions associated with social cognition and behavioral control, higher prosociality was associated with greater cortical thinning during early-to-middle adolescence, followed by attenuation of this process during the transition to young adulthood. Comparatively, lower prosociality was related to initially slower thinning, followed by comparatively protracted thinning into the mid-twenties. This study showed that prosocial behavior is associated with regional development of cortical thickness in adolescence and young adulthood. The results suggest that the rate of thinning in these regions, as well as its timing, may be factors related to prosocial behavior.
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Affiliation(s)
- Lia Ferschmann
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway.
| | | | - Håkon Grydeland
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway.
| | - Knut Overbye
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway.
| | - Donatas Sederevicius
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway.
| | - Paulina Due-Tønnessen
- Department of Radiology, Rikshospitalet, Oslo University Hospital, Department of Psychology, University of Oslo, Norway.
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway.
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway.
| | | | - Christian K Tamnes
- PROMENTA Research Center, Department of Psychology, University of Oslo, Department of Psychiatry, Diakonhjemmet Hospital, NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
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