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Jiang Y, Chen Y, Wei Y, Li S, Wang K, Cheng J. Integrative intrinsic brain activity and molecular analyses of the interaction between first-episode depression and age. J Affect Disord 2024; 367:129-136. [PMID: 39222854 DOI: 10.1016/j.jad.2024.08.207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Revised: 06/11/2024] [Accepted: 08/29/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND Numerous studies have underscored the presence of abnormal intrinsic neural activity (INA) in individuals with depression. However, recognizing that the age stage may influence the pathophysiology of depression, our study sought to delve into the interplay of depression and age on INA and molecular architecture. METHODS One hundred and thirty-eight first-episode depression patients and 120 healthy controls (HC) were recruited and underwent resting-state functional magnetic resonance imaging. The participants were stratified into four groups based on age. Utilizing amplitude of low-frequency fluctuation (ALFF) analyses, we employed an ANCOVA to compare INA patterns in four groups. Additionally, we conducted correlation analyses between ALFF and neurotransmitter maps to elucidate molecular underpinnings of INA abnormalities. RESULTS In comparison to adolescents with early-onset depression and adult HC, adult-onset depression exhibited increased ALFF in the right paracentral lobule. Conversely, early-onset depression, when contrasted with adolescent HC, displayed reduced ALFF in the right paracentral lobule. The interactive brain regions affected by ALFF alterations were associated with serotonergic, GABAergic, and opioid neurotransmitter systems. LIMITATIONS The present study was limited to its cross-sectional design. CONCLUSIONS This study illuminates an antagonistic effect of depression and age on brain activity in paracentral lobule and provides molecular underpinnings of the corresponding INA abnormalities related to key neurotransmitter systems. These insights may prove valuable in the development of neuromarkers for clinical intervention and treatment of depression.
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Affiliation(s)
- Yu Jiang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Ying Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Shuying Li
- Department of Psychiatry, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Kaiyu Wang
- MR Research China, GE Healthcare, Beijing 100000, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
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Holt-Gosselin B, Keding TJ, Poulin R, Brieant A, Rueter A, Hendrickson TJ, Perrone A, Byington N, Houghton A, Miranda-Dominguez O, Feczko E, Fair DA, Joormann J, Gee DG. Neural Circuit Markers of Familial Risk for Depression Among Healthy Youths in the Adolescent Brain Cognitive Development Study. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:185-195. [PMID: 37182734 PMCID: PMC10640659 DOI: 10.1016/j.bpsc.2023.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 05/01/2023] [Accepted: 05/02/2023] [Indexed: 05/16/2023]
Abstract
BACKGROUND Family history of depression is a robust predictor of early-onset depression, which may confer risk through alterations in neural circuits that have been implicated in reward and emotional processing. These alterations may be evident in youths who are at familial risk for depression but who do not currently have depression. However, the identification of robust and replicable findings has been hindered by few studies and small sample sizes. In the current study, we sought to identify functional connectivity (FC) patterns associated with familial risk for depression. METHODS Participants included healthy (i.e., no lifetime psychiatric diagnoses) youths at high familial risk for depression (HR) (n = 754; at least one parent with a history of depression) and healthy youths at low familial risk for psychiatric problems (LR) (n = 1745; no parental history of psychopathology) who were 9 to 10 years of age and from the Adolescent Brain Cognitive Development (ABCD) Study sample. We conducted whole-brain seed-to-voxel analyses to examine group differences in resting-state FC with the amygdala, caudate, nucleus accumbens, and putamen. We hypothesized that HR youths would exhibit global amygdala hyperconnectivity and striatal hypoconnectivity patterns primarily driven by maternal risk. RESULTS HR youths exhibited weaker caudate-angular gyrus FC than LR youths (α = 0.04, Cohen's d = 0.17). HR youths with a history of maternal depression specifically exhibited weaker caudate-angular gyrus FC (α = 0.03, Cohen's d = 0.19) as well as weaker caudate-dorsolateral prefrontal cortex FC (α = 0.04, Cohen's d = 0.21) than LR youths. CONCLUSIONS Weaker striatal connectivity may be related to heightened familial risk for depression, primarily driven by maternal history. Identifying brain-based markers of depression risk in youths can inform approaches to improving early detection, diagnosis, and treatment.
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Affiliation(s)
- Bailey Holt-Gosselin
- Department of Psychology, Yale University, New Haven, Connecticut; Interdepartmental Neuroscience Graduate Program, Yale University School of Medicine, New Haven, Connecticut
| | - Taylor J Keding
- Department of Psychology, Yale University, New Haven, Connecticut; Child Study Center, Yale School of Medicine, New Haven, Connecticut
| | - Rhayna Poulin
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Alexis Brieant
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Amanda Rueter
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Timothy J Hendrickson
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Anders Perrone
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Nora Byington
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Audrey Houghton
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | | | - Eric Feczko
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Damien A Fair
- Department of Pediatrics, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Jutta Joormann
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Dylan G Gee
- Department of Psychology, Yale University, New Haven, Connecticut.
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Wüthrich F, Lefebvre S, Mittal VA, Shankman SA, Alexander N, Brosch K, Flinkenflügel K, Goltermann J, Grotegerd D, Hahn T, Jamalabadi H, Jansen A, Leehr EJ, Meinert S, Nenadić I, Nitsch R, Stein F, Straube B, Teutenberg L, Thiel K, Thomas-Odenthal F, Usemann P, Winter A, Dannlowski U, Kircher T, Walther S. The neural signature of psychomotor disturbance in depression. Mol Psychiatry 2024; 29:317-326. [PMID: 38036604 PMCID: PMC11116107 DOI: 10.1038/s41380-023-02327-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Revised: 10/28/2023] [Accepted: 11/13/2023] [Indexed: 12/02/2023]
Abstract
Up to 70% of patients with major depressive disorder present with psychomotor disturbance (PmD), but at the present time understanding of its pathophysiology is limited. In this study, we capitalized on a large sample of patients to examine the neural correlates of PmD in depression. This study included 820 healthy participants and 699 patients with remitted (n = 402) or current (n = 297) depression. Patients were further categorized as having psychomotor retardation, agitation, or no PmD. We compared resting-state functional connectivity (ROI-to-ROI) between nodes of the cerebral motor network between the groups, including primary motor cortex, supplementary motor area, sensory cortex, superior parietal lobe, caudate, putamen, pallidum, thalamus, and cerebellum. Additionally, we examined network topology of the motor network using graph theory. Among the currently depressed 55% had PmD (15% agitation, 29% retardation, and 11% concurrent agitation and retardation), while 16% of the remitted patients had PmD (8% retardation and 8% agitation). When compared with controls, currently depressed patients with PmD showed higher thalamo-cortical and pallido-cortical connectivity, but no network topology alterations. Currently depressed patients with retardation only had higher thalamo-cortical connectivity, while those with agitation had predominant higher pallido-cortical connectivity. Currently depressed patients without PmD showed higher thalamo-cortical, pallido-cortical, and cortico-cortical connectivity, as well as altered network topology compared to healthy controls. Remitted patients with PmD showed no differences in single connections but altered network topology, while remitted patients without PmD did not differ from healthy controls in any measure. We found evidence for compensatory increased cortico-cortical resting-state functional connectivity that may prevent psychomotor disturbance in current depression, but may perturb network topology. Agitation and retardation show specific connectivity signatures. Motor network topology is slightly altered in remitted patients arguing for persistent changes in depression. These alterations in functional connectivity may be addressed with non-invasive brain stimulation.
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Affiliation(s)
- Florian Wüthrich
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.
- Graduate School of Health Science, University of Bern, Bern, Switzerland.
| | - Stephanie Lefebvre
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.
| | - Vijay A Mittal
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, USA
- Department of Psychology, Northwestern University, Evanston, IL, USA
- Northwestern University, Institute for Innovations in Developmental Sciences, Evanston/Chicago, IL, USA
- Northwestern University, Institute for Policy Research, Evanston, IL, USA
- Northwestern University, Medical Social Sciences, Chicago, IL, USA
| | - Stewart A Shankman
- Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, USA
- Department of Psychology, Northwestern University, Evanston, IL, USA
| | - Nina Alexander
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Kira Flinkenflügel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hamidreza Jamalabadi
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
- Core-Facility Brain imaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | - Elisabeth J Leehr
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Robert Nitsch
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), University of Marburg, Marburg, Germany
| | - Sebastian Walther
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
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Chang SE, Lenartowicz A, Hellemann GS, Uddin LQ, Bearden CE. Variability in Cognitive Task Performance in Early Adolescence Is Associated With Stronger Between-Network Anticorrelation and Future Attention Problems. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2023; 3:948-957. [PMID: 37881561 PMCID: PMC10593900 DOI: 10.1016/j.bpsgos.2022.11.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/22/2022] [Accepted: 11/09/2022] [Indexed: 11/28/2022] Open
Abstract
Background Intraindividual variability (IIV) during cognitive task performance is a key behavioral index of attention and a consistent marker of attention-deficit/hyperactivity disorder. In adults, lower IIV has been associated with anticorrelation between the default mode network (DMN) and dorsal attention network (DAN)-thought to underlie effective allocation of attention. However, whether these behavioral and neural markers of attention are 1) associated with each other and 2) can predict future attention-related deficits has not been examined in a developmental, population-based cohort. Methods We examined relationships at the baseline visit between IIV on 3 cognitive tasks, DMN-DAN anticorrelation, and parent-reported attention problems using data from the Adolescent Brain Cognitive Development (ABCD) Study (N = 11,878 participants, ages 9 to 10 years, female = 47.8%). We also investigated whether behavioral and neural markers of attention at baseline predicted attention problems 1, 2, and 3 years later. Results At baseline, greater DMN-DAN anticorrelation was associated with lower IIV across all 3 cognitive tasks (B = 0.22 to 0.25). Older age at baseline was associated with stronger DMN-DAN anticorrelation and lower IIV (B = -0.005 to -0.0004). Weaker DMN-DAN anticorrelation and IIV were cross-sectionally associated with attention problems (B = 1.41 to 7.63). Longitudinally, lower IIV at baseline was associated with less severe attention problems 1 to 3 years later, after accounting for baseline attention problems (B = 0.288 to 0.77). Conclusions The results suggest that IIV in early adolescence is associated with worsening attention problems in a representative cohort of U.S. youth. Attention deficits in early adolescence may be important for understanding and predicting future cognitive and clinical outcomes.
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Affiliation(s)
- Sarah E. Chang
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California
| | - Agatha Lenartowicz
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California
| | - Gerhard S. Hellemann
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California
- Department of Public Health, University of Alabama at Birmingham, Birmingham, Alabama
| | - Lucina Q. Uddin
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California
| | - Carrie E. Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, California
- Department of Psychology, University of California, Los Angeles, Los Angeles, California
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5
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Belleau EL, Kremens R, Bolton TA, Bondy E, Pisoni A, Auerbach RP, Pizzagalli DA. Default Mode and Frontoparietal Network Dynamics: Associations with Familial Risk for Depression and Stress Sensitivity. JOURNAL OF MOOD AND ANXIETY DISORDERS 2023; 1:100001. [PMID: 39193065 PMCID: PMC11349319 DOI: 10.1016/j.xjmad.2023.100001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/29/2024]
Abstract
Background Major Depressive Disorder (MDD) is associated with alterations within the default mode (DMN) and frontoparietal (FPN) networks. However, it is unclear whether changes in these networks occur prior to onset in youth at high familial risk for MDD or are a consequence of MDD. Moreover, studies examining premorbid MDD vulnerability markers have focused on static rather than dynamic network properties, which could further elucidate DMN-FPN imbalances linked to MDD risk. Methods Eighty-nine unaffected 12-14-year-old adolescents both with (n = 27) and without (n = 62) a maternal history of MDD completed a resting state functional magnetic resonance imaging scan and self-report assessments of depressive symptoms and perceived stress at baseline and every three months across a two-year span. A coactivation pattern (CAP) analysis was conducted to examine functional network dynamic properties, including time spent in each CAP (total number of volumes), CAP persistence (number of consecutive volumes in each CAP), and number of transitions between posterior DMN-FPN and canonical DMN CAPs. Multilevel models estimated whether DMN-FPN dynamic properties predicted future depressive symptoms and stress sensitivity. Results High-risk adolescents spent more time and exhibited a longer persistence in a posterior DMN-FPN CAP. DMN-FPN CAP persistence predicted future perceived stress, but only among high-risk adolescents. High-risk adolescents characterized by high DMN-FPN persistence reported greater future perceived stress, whereas those showing low DMN-FPN persistence had reduced perceived stress over time. Unexpectedly, DMN-FPN dynamics did not predict future depressive symptoms. Conclusions Altered DMN-FPN CAP properties among high-risk adolescents mirror alterations among individuals with MDD, suggesting that DMN-FPN dynamics may be a risk marker rather than consequence of MDD. Furthermore, longer DMN-FPN CAP persistence increases vulnerability in high-risk adolescents by predicting greater future stress sensitivity, a well-known catalyst for MDD. Replication in a larger sample is warranted.
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Affiliation(s)
- Emily L. Belleau
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Rebecca Kremens
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Thomas A.W. Bolton
- Connectomics Laboratory, Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Erin Bondy
- Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA
| | - Angela Pisoni
- Department of Psychology & Neuroscience, Duke University, Durham, NC, USA
| | - Randy P. Auerbach
- Department of Psychiatry, Columbia University, New York, NY, USA
- Division of Clinical Developmental Neuroscience, Sackler Institute, New York, NY, USA
| | - Diego A. Pizzagalli
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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Dall'Aglio L, Estévez-López F, López-Vicente M, Xu B, Agcaoglu O, Boroda E, Lim KO, Calhoun VD, Tiemeier H, Muetzel RL. Exploring the longitudinal associations of functional network connectivity and psychiatric symptom changes in youth. Neuroimage Clin 2023; 38:103382. [PMID: 36965455 PMCID: PMC10074199 DOI: 10.1016/j.nicl.2023.103382] [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: 12/09/2022] [Revised: 03/06/2023] [Accepted: 03/14/2023] [Indexed: 03/22/2023]
Abstract
BACKGROUND Functional connectivity has been associated with psychiatric problems, both in children and adults, but inconsistencies are present across studies. Prior research has mostly focused on small clinical samples with cross-sectional designs. METHODS We adopted a longitudinal design with repeated assessments to investigate associations between functional network connectivity (FNC) and psychiatric problems in youth (9- to 17-year-olds, two time points) from the general population. The largest single-site study of pediatric neurodevelopment was used: Generation R (N = 3,131 with data at either time point). Psychiatric symptoms were measured with the Child Behavioral Checklist as broadband internalizing and externalizing problems, and its eight specific syndrome scales (e.g., anxious-depressed). FNC was assessed with two complementary approaches. First, static FNC (sFNC) was measured with graph theory-based metrics. Second, dynamic FNC (dFNC), where connectivity is allowed to vary over time, was summarized into 5 states that participants spent time in. Cross-lagged panel models were used to investigate the longitudinal bidirectional relationships of sFNC with internalizing and externalizing problems. Similar cross-lagged panel models were run for dFNC. RESULTS Small longitudinal relationships between dFNC and certain syndrome scales were observed, especially for baseline syndrome scales (i.e., rule-breaking, somatic complaints, thought problems, and attention problems) predicting connectivity changes. However, no association between any of the psychiatric problems (broadband and syndrome scales) with either measure of FNC survived correction for multiple testing. CONCLUSION We found no or very modest evidence for longitudinal associations between psychiatric problems with dynamic and static FNC in this population-based sample. Differences in findings may stem from the population drawn, study design, developmental timing, and sample sizes.
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Affiliation(s)
- Lorenza Dall'Aglio
- Department of Child and Adolescent Psychology and Psychiatry, Erasmus MC, Rotterdam, The Netherlands; The Generation R Study Group, Erasmus MC, Rotterdam, The Netherlands
| | - Fernando Estévez-López
- Department of Social and Behavioral Sciences, Harvard T. Chan School of Public Health, Boston, USA
| | - Mónica López-Vicente
- Department of Child and Adolescent Psychology and Psychiatry, Erasmus MC, Rotterdam, The Netherlands; The Generation R Study Group, Erasmus MC, Rotterdam, The Netherlands
| | - Bing Xu
- Department of Child and Adolescent Psychology and Psychiatry, Erasmus MC, Rotterdam, The Netherlands; The Generation R Study Group, Erasmus MC, Rotterdam, The Netherlands
| | - Oktay Agcaoglu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, USA
| | - Elias Boroda
- Department of Psychiatry and Behavioral Science, University of Minnesota, Minneapolis, USA
| | - Kelvin O Lim
- Department of Psychiatry and Behavioral Science, University of Minnesota, Minneapolis, USA
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, USA
| | - Henning Tiemeier
- Department of Child and Adolescent Psychology and Psychiatry, Erasmus MC, Rotterdam, The Netherlands; Department of Social and Behavioral Sciences, Harvard T. Chan School of Public Health, Boston, USA.
| | - Ryan L Muetzel
- Department of Child and Adolescent Psychology and Psychiatry, Erasmus MC, Rotterdam, The Netherlands
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7
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Lawrence KE, Abaryan Z, Laltoo E, Hernandez LM, Gandal MJ, McCracken JT, Thompson PM. White matter microstructure shows sex differences in late childhood: Evidence from 6797 children. Hum Brain Mapp 2023; 44:535-548. [PMID: 36177528 PMCID: PMC9842921 DOI: 10.1002/hbm.26079] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 07/29/2022] [Accepted: 08/19/2022] [Indexed: 02/01/2023] Open
Abstract
Sex differences in white matter microstructure have been robustly demonstrated in the adult brain using both conventional and advanced diffusion-weighted magnetic resonance imaging approaches. However, sex differences in white matter microstructure prior to adulthood remain poorly understood; previous developmental work focused on conventional microstructure metrics and yielded mixed results. Here, we rigorously characterized sex differences in white matter microstructure among over 6000 children from the Adolescent Brain Cognitive Development study who were between 9 and 10 years old. Microstructure was quantified using both the conventional model-diffusion tensor imaging (DTI)-and an advanced model, restriction spectrum imaging (RSI). DTI metrics included fractional anisotropy (FA) and mean, axial, and radial diffusivity (MD, AD, RD). RSI metrics included normalized isotropic, directional, and total intracellular diffusion (N0, ND, NT). We found significant and replicable sex differences in DTI or RSI microstructure metrics in every white matter region examined across the brain. Sex differences in FA were regionally specific. Across white matter regions, boys exhibited greater MD, AD, and RD than girls, on average. Girls displayed increased N0, ND, and NT compared to boys, on average, suggesting greater cell and neurite density in girls. Together, these robust and replicable findings provide an important foundation for understanding sex differences in health and disease.
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Affiliation(s)
- Katherine E. Lawrence
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Zvart Abaryan
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Emily Laltoo
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Leanna M. Hernandez
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Michael J. Gandal
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los AngelesLos AngelesCaliforniaUSA
- Department of Neurology, Center for Autism Research and Treatment, Semel Institute, David Geffen School of MedicineUniversity of California Los AngelesLos AngelesCaliforniaUSA
- Department of Human Genetics, David Geffen School of MedicineUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - James T. McCracken
- Department of Psychiatry and Biobehavioral SciencesUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics InstituteUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
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Structural and Functional Brain Alterations in Populations with Familial Risk for Depression: A Narrative Review. Harv Rev Psychiatry 2022; 30:327-349. [PMID: 36534836 DOI: 10.1097/hrp.0000000000000350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
LEARNING OBJECTIVES After completing this activity, practitioners will be better able to:• Discuss the association between brain alterations and vulnerability or resilience to MDD in people with familial risk• Define how structural and functional brain alterations associated with vulnerability or resilience could lead to a better understanding of the pathophysiology of MDD. AIM Familial history is associated with an increased risk for major depressive disorder (MDD). Despite the increased risk, some members of the familial high-risk population remain healthy, that is, resilient. Defining the structural and functional brain alterations associated with vulnerability or resilience could lead to a better understanding of the pathophysiology of MDD. This study aimed to review the current literature and discuss the association between brain alterations and vulnerability or resilience to MDD in people with familial risk. METHODS A literature search on MRI studies investigating structural and functional alterations in populations at familial risk for MDD was performed using the PubMed and SCOPUS databases. The search was conducted through June 13, 2022. RESULTS We reviewed and summarized the data of 72 articles (25 structural MRI, 35 functional MRI, 10 resting-state fMRI, one structural/functional MRI combined, and one structural/functional/resting-state fMRI combined). These findings suggested that resilience in high-risk individuals is related to the amygdala structure, frontal lobe activity, and functional connectivity between the amygdala and multiple frontal regions. CONCLUSION Resilient and vulnerable individuals exhibit structural and functional differences in multiple frontal and limbic regions. However, further systematic longitudinal research incorporating environmental factors is required to validate the current findings.
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Sun JF, Chen LM, He JK, Wang Z, Guo CL, Ma Y, Luo Y, Gao DQ, Hong Y, Fang JL, Xu FQ. A Comparative Study of Regional Homogeneity of Resting-State fMRI Between the Early-Onset and Late-Onset Recurrent Depression in Adults. Front Psychol 2022; 13:849847. [PMID: 35465554 PMCID: PMC9021891 DOI: 10.3389/fpsyg.2022.849847] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/11/2022] [Indexed: 12/24/2022] Open
Abstract
Background Neurobiological mechanisms underlying the recurrence of major depressive disorder (MDD) at different ages are unclear, and this study used the regional homogeneity (ReHo) index to compare whether there are differences between early onset recurrent depression (EORD) and late onset recurrent depression (LORD). Methods Eighteen EORD patients, 18 LORD patients, 18 young healthy controls (HCs), and 18 older HCs were included in the rs-fMRI scans. ReHo observational metrics were used for image analysis and further correlation of differential brain regions with clinical symptoms was analyzed. Results ANOVA analysis revealed significant differences between the four groups in ReHo values in the prefrontal, parietal, temporal lobes, and insula. Compared with EORD, the LORD had higher ReHo in the right fusiform gyrus/right middle temporal gyrus, left middle temporal gyrus/left angular gyrus, and right middle temporal gyrus/right angular gyrus, and lower ReHo in the right inferior frontal gyrus/right insula and left superior temporal gyrus/left insula. Compared with young HCs, the EORD had higher ReHo in the right inferior frontal gyrus/right insula, left superior temporal gyrus/left insula, and left rolandic operculum gyrus/left superior temporal gyrus, and lower ReHo in the left inferior parietal lobule, right inferior parietal lobule, and left middle temporal gyrus/left angular gyrus. Compared with old HCs, the LORD had higher ReHo in the right fusiform gyrus/right middle temporal gyrus, right middle temporal gyrus/right angular gyrus, and left rolandic operculum gyrus/left superior temporal gyrus, and lower ReHo in the right inferior frontal gyrus/right insula. ReHo in the right inferior frontal gyrus/right insula of patients with LORD was negatively correlated with the severity of 17-item Hamilton Rating Scale for Depression (HAMD-17) scores (r = −0.5778, p = 0.0120). Conclusion Adult EORD and LORD patients of different ages have abnormal neuronal functional activity in some brain regions, with differences closely related to the default mode network (DMN) and the salience network (SN), and patients of each age group exhibit ReHo abnormalities relative to matched HCs. Clinical Trial Registration [http://www.chictr.org.cn/], [ChiCTR1800014277].
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Affiliation(s)
- Ji-Fei Sun
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.,Graduate School of China Academy of Chinese Medical Sciences, Beijing, China
| | - Li-Mei Chen
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.,Graduate School of China Academy of Chinese Medical Sciences, Beijing, China
| | - Jia-Kai He
- Graduate School of China Academy of Chinese Medical Sciences, Beijing, China.,Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zhi Wang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.,Graduate School of China Academy of Chinese Medical Sciences, Beijing, China
| | - Chun-Lei Guo
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.,Graduate School of China Academy of Chinese Medical Sciences, Beijing, China
| | - Yue Ma
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.,Graduate School of China Academy of Chinese Medical Sciences, Beijing, China
| | - Yi Luo
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.,Graduate School of China Academy of Chinese Medical Sciences, Beijing, China
| | - De-Qiang Gao
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yang Hong
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Ji-Liang Fang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Feng-Quan Xu
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
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10
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Qin K, Lei D, Pinaya WHL, Pan N, Li W, Zhu Z, Sweeney JA, Mechelli A, Gong Q. Using graph convolutional network to characterize individuals with major depressive disorder across multiple imaging sites. EBioMedicine 2022; 78:103977. [PMID: 35367775 PMCID: PMC8983334 DOI: 10.1016/j.ebiom.2022.103977] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 03/01/2022] [Accepted: 03/16/2022] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Establishing objective and quantitative neuroimaging biomarkers at individual level can assist in early and accurate diagnosis of major depressive disorder (MDD). However, most previous studies using machine learning to identify MDD were based on small sample size and did not account for the brain connectome that is associated with the pathophysiology of MDD. Here, we addressed these limitations by applying graph convolutional network (GCN) in a large multi-site MDD dataset. METHODS Resting-state functional MRI scans of 1586 participants (821 MDD vs. 765 controls) across 16 sites of Rest-meta-MDD consortium were collected. GCN model was trained with individual whole-brain functional network to identify MDD patients from controls, characterize the most salient regions contributing to classification, and explore the relationship between topological characteristics of salient regions and clinical measures. FINDINGS GCN achieved an accuracy of 81·5% (95%CI: 80·5-82·5%, AUC: 0·865), which was higher than other common machine learning classifiers. The most salient regions contributing to classification were primarily identified within the default mode, fronto-parietal, and cingulo-opercular networks. Nodal topologies of the left inferior parietal lobule and left dorsolateral prefrontal cortex were associated with depressive severity and illness duration, respectively. INTERPRETATION These findings based on a large, multi-site dataset support the feasibility and effectiveness of GCN in characterizing MDD, and also illustrate the potential utility of GCN for enhancing understanding of the neurobiology of MDD by detecting clinically-relevant disruption in functional network topology. FUNDING This study was supported by the National Natural Science Foundation of China (Grant Nos. 81621003, 82027808, 81820108018).
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Affiliation(s)
- Kun Qin
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA; Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Du Lei
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Walter H L Pinaya
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Nanfang Pan
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China; Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Wenbin Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Ziyu Zhu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China; Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London, UK
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China; Department of Radiology, West China Xiamen Hospital of Sichuan University, Xiamen, Fujian, China.
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11
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Damme KS, Park JS, Vargas T, Walther S, Shankman SA, Mittal VA. Motor abnormalities, depression risk, and clinical course in adolescence. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2022; 2:61-69. [PMID: 35419552 PMCID: PMC9000199 DOI: 10.1016/j.bpsgos.2021.06.011] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/25/2021] [Accepted: 06/26/2021] [Indexed: 02/02/2023] Open
Abstract
Background Motor abnormalities, such as psychomotor agitation and retardation, are widely recognized as core features of depression. However, it is not currently known if motor abnormalities connote risk for depression. Methods Using data from the Adolescent Brain Cognitive Development (ABCD) Study, a nationally representative sample of youth (n=10,835, 9-11 years old), the present paper examines whether motor abnormalities are associated with (a) depression symptoms in early adolescence, (b) familial risk for depression (familial risk loading), and (c) future depression symptoms. Motor abnormalities measures included traditional (DSM) motor signs such as psychomotor agitation and retardation as well as other motor domains such as developmental motor delays and dyscoordination. Results Traditional motor abnormalities were less prevalent (agitation=3.2%, retardation=0.3%) than non-traditional domains (delays=13.79%, coordination=35.5%) among adolescents. Motor dysfunction was associated with depression symptoms (Cohen's ds=0.02 to 0.12). Familial risk for depression was related to motor abnormalities (Cohen's ds=0.08 to 0.27), with the exception of motor retardation. Family vulnerability varied in sensitivity to depression risk (e.g., retardation: .53%; dyscoordination: 32.05%). Baseline endorsement of motor abnormalities predicted future depression symptoms at one-year follow-up. Conclusions These findings suggest that motor signs reflect a novel, promising future direction for examining vulnerability to depression risk in early adolescence.
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Affiliation(s)
- Katherine S.F. Damme
- Department of Psychology, Northwestern University, Evanston, Illinois
- Institute for Innovations in Developmental Sciences, Northwestern University, Evanston and Chicago, Illinois
| | - Jadyn S. Park
- Department of Psychology, Northwestern University, Evanston, Illinois
- Department of Psychiatry, Northwestern University, Chicago, Illinois
| | - Teresa Vargas
- Department of Psychology, Northwestern University, Evanston, Illinois
- Institute for Innovations in Developmental Sciences, Northwestern University, Evanston and Chicago, Illinois
| | - Sebastian Walther
- Translational Research Center, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - Stewart A. Shankman
- Department of Psychology, Northwestern University, Evanston, Illinois
- Institute for Innovations in Developmental Sciences, Northwestern University, Evanston and Chicago, Illinois
- Department of Psychiatry, Northwestern University, Chicago, Illinois
| | - Vijay A. Mittal
- Department of Psychology, Northwestern University, Evanston, Illinois
- Institute for Innovations in Developmental Sciences, Northwestern University, Evanston and Chicago, Illinois
- Medical Social Sciences, Northwestern University, Chicago, Illinois
- Institute for Policy Research, Northwestern University, Chicago, Illinois
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