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Gálber M, Anett Nagy S, Orsi G, Perlaki G, Simon M, Czéh B. Depressed patients with childhood maltreatment display altered intra- and inter-network resting state functional connectivity. Neuroimage Clin 2024; 43:103632. [PMID: 38889524 PMCID: PMC11231604 DOI: 10.1016/j.nicl.2024.103632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 04/05/2024] [Accepted: 06/11/2024] [Indexed: 06/20/2024]
Abstract
BACKGROUND Childhood maltreatment (CM) is a major risk factor for the development of major depressive disorder (MDD). To gain more knowledge on how adverse childhood experiences influence the development of brain architecture, we studied functional connectivity (FC) alterations of neural networks of depressed patients with, or without the history of CM. METHODS Depressed patients with severe childhood maltreatment (n = 18), MDD patients without maltreatment (n = 19), and matched healthy controls (n = 20) were examined with resting state functional MRI. History of maltreatment was assessed with the 28-item Childhood Trauma Questionnaire. Intra- and inter-network FC alterations were evaluated using FMRIB Software Library and CONN toolbox. RESULTS We found numerous intra- and inter-network FC alterations between the maltreated and the non-maltreated patients. Intra-network FC differences were found in the default mode, visual and auditory networks, and cerebellum. Network modelling revealed several inter-network FC alterations connecting the default mode network with the executive control, salience and cerebellar networks. Increased inter-network FC was found in maltreated patients between the sensory-motor and visual, cerebellar, default mode and salience networks. LIMITATIONS Relatively small sample size, cross-sectional design, and retrospective self-report questionnaire to assess adverse childhood experiences. CONCLUSIONS Our findings confirm that severely maltreated depressed patients display numerous alterations of intra- and inter-network FC strengths, not only in their fronto-limbic circuits, but also in sensory-motor, visual, auditory, and cerebellar networks. These functional alterations may explain that maltreated individuals typically display altered perception and are prone to develop functional neurological symptom disorder (conversion disorder) in adulthood.
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Affiliation(s)
- Mónika Gálber
- Neurobiology of Stress Research Group, Szentágothai Research Centre, University of Pécs, Pécs, Hungary; Department of Laboratory Medicine, Medical School, University of Pécs, Pécs, Hungary
| | - Szilvia Anett Nagy
- Neurobiology of Stress Research Group, Szentágothai Research Centre, University of Pécs, Pécs, Hungary; HUN-REN-PTE Clinical Neuroscience MR Research Group, Pécs, Hungary; Department of Neurosurgery, Medical School, University of Pécs, Pécs, Hungary; Pécs Diagnostic Centre, Pécs, Hungary
| | - Gergely Orsi
- HUN-REN-PTE Clinical Neuroscience MR Research Group, Pécs, Hungary; Department of Neurosurgery, Medical School, University of Pécs, Pécs, Hungary; Pécs Diagnostic Centre, Pécs, Hungary; Department of Neurology, Medical School, University of Pécs, Hungary
| | - Gábor Perlaki
- HUN-REN-PTE Clinical Neuroscience MR Research Group, Pécs, Hungary; Department of Neurosurgery, Medical School, University of Pécs, Pécs, Hungary; Pécs Diagnostic Centre, Pécs, Hungary; Department of Neurology, Medical School, University of Pécs, Hungary
| | - Maria Simon
- Neurobiology of Stress Research Group, Szentágothai Research Centre, University of Pécs, Pécs, Hungary; Department of Psychiatry and Psychotherapy, Medical School, University of Pécs, Hungary
| | - Boldizsár Czéh
- Neurobiology of Stress Research Group, Szentágothai Research Centre, University of Pécs, Pécs, Hungary; Department of Laboratory Medicine, Medical School, University of Pécs, Pécs, Hungary.
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Lee K, Ji JL, Fonteneau C, Berkovitch L, Rahmati M, Pan L, Repovš G, Krystal JH, Murray JD, Anticevic A. Human brain state dynamics reflect individual neuro-phenotypes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.18.557763. [PMID: 37790400 PMCID: PMC10542143 DOI: 10.1101/2023.09.18.557763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Neural activity and behavior vary within an individual (states) and between individuals (traits). However, the mapping of state-trait neural variation to behavior is not well understood. To address this gap, we quantify moment-to-moment changes in brain-wide co-activation patterns derived from resting-state functional magnetic resonance imaging. In healthy young adults, we identify reproducible spatio-temporal features of co-activation patterns at the single subject level. We demonstrate that a joint analysis of state-trait neural variations and feature reduction reveal general motifs of individual differences, encompassing state-specific and general neural features that exhibit day-to-day variability. The principal neural variations co-vary with the principal variations of behavioral phenotypes, highlighting cognitive function, emotion regulation, alcohol and substance use. Person-specific probability of occupying a particular co-activation pattern is reproducible and associated with neural and behavioral features. This combined analysis of state-trait variations holds promise for developing reproducible neuroimaging markers of individual life functional outcome.
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Affiliation(s)
- Kangjoo Lee
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Jie Lisa Ji
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Clara Fonteneau
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Lucie Berkovitch
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Saclay CEA Centre, Neurospin, Gif-Sur-Yvette Cedex, France
- Department of Psychiatry, GHU Paris Psychiatrie et Neurosciences, Service Hospitalo-Universitaire, Paris, France
- Université Paris Cité, 15 Rue de l'École de Médecine, F-75006 Paris, France
| | - Masih Rahmati
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Lining Pan
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Grega Repovš
- Department of Psychology, University of Ljubljana, Ljubljana, Slovenia
| | - John H Krystal
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - John D Murray
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, USA
- Department of Physics, Yale University, New Haven, CT, USA
| | - Alan Anticevic
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychology, Yale University School of Medicine, New Haven, CT, USA
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3
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Dan R, Whitton AE, Treadway MT, Rutherford AV, Kumar P, Ironside ML, Kaiser RH, Ren B, Pizzagalli DA. Brain-based graph-theoretical predictive modeling to map the trajectory of anhedonia, impulsivity, and hypomania from the human functional connectome. Neuropsychopharmacology 2024; 49:1162-1170. [PMID: 38480910 PMCID: PMC11109096 DOI: 10.1038/s41386-024-01842-1] [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: 10/20/2023] [Revised: 01/27/2024] [Accepted: 03/01/2024] [Indexed: 03/26/2024]
Abstract
Clinical assessments often fail to discriminate between unipolar and bipolar depression and identify individuals who will develop future (hypo)manic episodes. To address this challenge, we developed a brain-based graph-theoretical predictive model (GPM) to prospectively map symptoms of anhedonia, impulsivity, and (hypo)mania. Individuals seeking treatment for mood disorders (n = 80) underwent an fMRI scan, including (i) resting-state and (ii) a reinforcement-learning (RL) task. Symptoms were assessed at baseline as well as at 3- and 6-month follow-ups. A whole-brain functional connectome was computed for each fMRI task, and the GPM was applied for symptom prediction using cross-validation. Prediction performance was evaluated by comparing the GPM to a corresponding null model. In addition, the GPM was compared to the connectome-based predictive modeling (CPM). Cross-sectionally, the GPM predicted anhedonia from the global efficiency (a graph theory metric that quantifies information transfer across the connectome) during the RL task, and impulsivity from the centrality (a metric that captures the importance of a region) of the left anterior cingulate cortex during resting-state. At 6-month follow-up, the GPM predicted (hypo)manic symptoms from the local efficiency of the left nucleus accumbens during the RL task and anhedonia from the centrality of the left caudate during resting-state. Notably, the GPM outperformed the CPM, and GPM derived from individuals with unipolar disorders predicted anhedonia and impulsivity symptoms for individuals with bipolar disorders. Importantly, the generalizability of cross-sectional models was demonstrated in an external validation sample. Taken together, across DSM mood diagnoses, efficiency and centrality of the reward circuit predicted symptoms of anhedonia, impulsivity, and (hypo)mania, cross-sectionally and prospectively. The GPM is an innovative modeling approach that may ultimately inform clinical prediction at the individual level.
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Affiliation(s)
- Rotem Dan
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Alexis E Whitton
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Black Dog Institute, University of New South Wales, Sydney, Australia
| | - Michael T Treadway
- Department of Psychology, Emory University, Atlanta, GA, USA
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA
| | - Ashleigh V Rutherford
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Poornima Kumar
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Manon L Ironside
- Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Roselinde H Kaiser
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Boyu Ren
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Laboratory for Psychiatric Biostatistics, McLean Hospital, Belmont, MA, 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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4
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Dong D, Pizzagalli DA, Bolton TAW, Ironside M, Zhang X, Li C, Sun X, Xiong G, Cheng C, Wang X, Yao S, Belleau EL. Sex-specific resting state brain network dynamics in patients with major depressive disorder. Neuropsychopharmacology 2024; 49:806-813. [PMID: 38218921 PMCID: PMC10948777 DOI: 10.1038/s41386-024-01799-1] [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: 06/19/2023] [Revised: 01/01/2024] [Accepted: 01/04/2024] [Indexed: 01/15/2024]
Abstract
Sex-specific neurobiological changes have been implicated in Major Depressive Disorder (MDD). Dysfunctions of the default mode network (DMN), salience network (SN) and frontoparietal network (FPN) are critical neural characteristics of MDD, however, the potential moderating role of sex on resting-state network dynamics in MDD has not been sufficiently evaluated. Thus, resting-state functional magnetic resonance imaging (fMRI) data were collected from 138 unmedicated patients with first-episode MDD (55 males) and 243 healthy controls (HCs; 106 males). Recurring functional network co-activation patterns (CAPs) were extracted, and time spent in each CAP (the total amount of volumes associated to a CAP), persistence (the average number of consecutive volumes linked to a CAP), and transitions across CAPs involving the SN, DMN and FPN were quantified. Relative to HCs, MDD patients exhibited greater persistence in a CAP involving activation of the DMN and deactivation of the FPN (DMN + FPN-). In addition, relative to the sex-matched HCs, the male MDD group spent more time in two CAPs involving the SN and DMN (i.e., DMN + SN- and DMN-SN + ) and transitioned more frequently from the DMN + FPN- CAP to the DMN + SN- CAP relative to the male HC group. Conversely, the female MDD group showed less persistence in the DMN + SN- CAP relative to the female HC group. Our findings highlight that the imbalance between SN and DMN could be a neurobiological marker supporting sex differences in MDD. Moreover, the dominance of the DMN accompanied by the deactivation of the FPN could be a sex-independent neurobiological correlate related to depression.
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Affiliation(s)
- Daifeng Dong
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
- China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Diego A Pizzagalli
- McLean Hospital, Belmont, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Thomas A W Bolton
- Connectomics Laboratory, Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Maria Ironside
- McLean Hospital, Belmont, MA, USA
- Harvard Medical School, Boston, MA, USA
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Xiaocui Zhang
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
- China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Chuting Li
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
- China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Xiaoqiang Sun
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
- China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Ge Xiong
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
- China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Chang Cheng
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
- China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China
- China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China
| | - Shuqiao Yao
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, PR China.
- China National Clinical Research Center for Mental Disorders (Xiangya), Changsha, Hunan, PR China.
| | - Emily L Belleau
- McLean Hospital, Belmont, MA, USA.
- Harvard Medical School, Boston, MA, USA.
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5
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Clancy KJ, Devignes Q, Ren B, Pollmann Y, Nielsen SR, Howell K, Kumar P, Belleau EL, Rosso IM. Spatiotemporal dynamics of hippocampal-cortical networks underlying the unique phenomenological properties of trauma-related intrusive memories. Mol Psychiatry 2024:10.1038/s41380-024-02486-9. [PMID: 38454081 DOI: 10.1038/s41380-024-02486-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 02/07/2024] [Accepted: 02/12/2024] [Indexed: 03/09/2024]
Abstract
Trauma-related intrusive memories (TR-IMs) possess unique phenomenological properties that contribute to adverse post-traumatic outcomes, positioning them as critical intervention targets. However, transdiagnostic treatments for TR-IMs are scarce, as their underlying mechanisms have been investigated separate from their unique phenomenological properties. Extant models of more general episodic memory highlight dynamic hippocampal-cortical interactions that vary along the anterior-posterior axis of the hippocampus (HPC) to support different cognitive-affective and sensory-perceptual features of memory. Extending this work into the unique properties of TR-IMs, we conducted a study of eighty-four trauma-exposed adults who completed daily ecological momentary assessments of TR-IM properties followed by resting-state functional magnetic resonance imaging (rs-fMRI). Spatiotemporal dynamics of anterior and posterior hippocampal (a/pHPC)-cortical networks were assessed using co-activation pattern analysis to investigate their associations with different properties of TR-IMs. Emotional intensity of TR-IMs was inversely associated with the frequency and persistence of an aHPC-default mode network co-activation pattern. Conversely, sensory features of TR-IMs were associated with more frequent co-activation of the HPC with sensory cortices and the ventral attention network, and the reliving of TR-IMs in the "here-and-now" was associated with more persistent co-activation of the pHPC and the visual cortex. Notably, no associations were found between HPC-cortical network dynamics and conventional symptom measures, including TR-IM frequency or retrospective recall, underscoring the utility of ecological assessments of memory properties in identifying their neural substrates. These findings provide novel insights into the neural correlates of the unique features of TR-IMs that are critical for the development of individualized, transdiagnostic treatments for this pervasive, difficult-to-treat symptom.
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Affiliation(s)
- Kevin J Clancy
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Quentin Devignes
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Boyu Ren
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Laboratory for Psychiatric Biostatistics, McLean Hospital, Belmont, MA, USA
| | - Yara Pollmann
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Sienna R Nielsen
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Kristin Howell
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - Poornima Kumar
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Emily L Belleau
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Isabelle M Rosso
- 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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An Z, Tang K, Xie Y, Tong C, Liu J, Tao Q, Feng Y. Aberrant resting-state co-activation network dynamics in major depressive disorder. Transl Psychiatry 2024; 14:1. [PMID: 38172115 PMCID: PMC10764934 DOI: 10.1038/s41398-023-02722-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 12/04/2023] [Accepted: 12/19/2023] [Indexed: 01/05/2024] Open
Abstract
Major depressive disorder (MDD) is a globally prevalent and highly disabling disease characterized by dysfunction of large-scale brain networks. Previous studies have found that static functional connectivity is not sufficient to reflect the complicated and time-varying properties of the brain. The underlying dynamic interactions between brain functional networks of MDD remain largely unknown, and it is also unclear whether neuroimaging-based dynamic properties are sufficiently robust to discriminate individuals with MDD from healthy controls since the diagnosis of MDD mainly depends on symptom-based criteria evaluated by clinical observation. Resting-state functional magnetic resonance imaging (fMRI) data of 221 MDD patients and 215 healthy controls were shared by REST-meta-MDD consortium. We investigated the spatial-temporal dynamics of MDD using co-activation pattern analysis and made individual diagnoses using support vector machine (SVM). We found that MDD patients exhibited aberrant dynamic properties (such as dwell time, occurrence rate, transition probability, and entropy of Markov trajectories) in some transient networks including subcortical network (SCN), activated default mode network (DMN), de-activated SCN-cerebellum network, a joint network, activated attention network (ATN), and de-activated DMN-ATN, where some dynamic properties were indicative of depressive symptoms. The trajectories of other networks to deactivated DMN-ATN were more accessible in MDD patients. Subgroup analyses also showed subtle dynamic changes in first-episode drug-naïve (FEDN) MDD patients. Finally, SVM achieved preferable accuracies of 84.69%, 76.77%, and 88.10% in discriminating patients with MDD, FEDN MDD, and recurrent MDD from healthy controls with their dynamic metrics. Our findings reveal that MDD is characterized by aberrant dynamic fluctuations of brain network and the feasibility of discriminating MDD patients using dynamic properties, which provide novel insights into the neural mechanism of MDD.
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Affiliation(s)
- Ziqi An
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Kai Tang
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Yuanyao Xie
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Chuanjun Tong
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Institute of Neuroscience, CAS Key Laboratory of Primate Neurobiology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Jiaming Liu
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde), Foshan, China
| | - Quan Tao
- Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Yanqiu Feng
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
- Department of Radiology, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde), Foshan, China.
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong Province Key Laboratory of Psychiatric Disorders, Department of Neurobiology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, 510515, China.
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7
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Quam A, Biernacki K, Ross TJ, Salmeron BJ, Janes AC. Childhood Trauma, Emotional Awareness, and Neural Correlates of Long-Term Nicotine Smoking. JAMA Netw Open 2024; 7:e2351132. [PMID: 38206627 PMCID: PMC10784870 DOI: 10.1001/jamanetworkopen.2023.51132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Accepted: 11/21/2023] [Indexed: 01/12/2024] Open
Abstract
Importance Temporal dynamic measures provide insight into the neurobiological properties of nicotine use. It is critical to determine whether brain-based measures are associated with substance use risk factors, such as childhood trauma-related emotion dysregulation. Objective To assess temporal dynamic differences based on smoking status and examine the associations between childhood trauma, alexithymia, nicotine smoking, and default mode network (DMN) states. Design, Setting, and Participants This cross-sectional study was conducted in the Baltimore, Maryland, area at the National Institute on Drug Abuse. Participants included individuals aged 18 to 65 years who smoked nicotine long term and matched controls with no co-occurring substance use or psychiatric disorders. Participants were enrolled from August 8, 2013, to August 9, 2022. Analysis was conducted from August 2022 to July 2023. Exposure Long-term nicotine smoking. Main Outcomes and Measures The main outcome was temporal dynamic differences based on smoking status. Coactivation pattern analysis was conducted based on 16-minute resting-state functional magnetic resonance imaging; total time in, persistence of, and frequency of transitions into states were evaluated. The associations between childhood trauma (Childhood Trauma Questionnaire), alexithymia (20-item Toronto Alexithymia Scale), and DMN temporal dynamics were assessed. Results The sample included 204 participants (102 individuals who smoked nicotine and 102 control individuals) with a mean (SD) age of 37.53 (10.64) years (109 [53.4%] male). Compared with controls, individuals who smoked nicotine spent more time in the frontoinsular DMN (FI-DMN) state (mean difference, 25.63 seconds; 95% CI, 8.05-43.20 seconds; η2p = 0.04; P = .004 after Bonferroni correction). In those who smoked nicotine, greater alexithymia was associated with less time spent in the FI-DMN state (r, -0.26; 95% CI, -0.44 to -0.07; P = .007). In a moderated mediation analysis, alexithymia mediated the association between childhood trauma and time spent in the FI-DMN state only in individuals who smoked nicotine (c' = -0.24; 95% CI, -0.58 to -0.03; P = .02). Conclusions and Relevance Compared with controls, individuals who smoked nicotine spent more time in the FI-DMN state. Among those who smoked nicotine, childhood trauma-related alexithymia was associated with less time spent in the FI-DMN state, indicating that considering trauma-related factors may reveal alternative neurobiological underpinnings of substance use. These data may aid in reconciling contradictory findings in prior literature regarding the role of FI-DMN regions in substance use.
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Affiliation(s)
- Annika Quam
- Neuroimaging Research Branch, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, Maryland
| | - Kathryn Biernacki
- Neuroimaging Research Branch, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, Maryland
| | - Thomas J. Ross
- Neuroimaging Research Branch, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, Maryland
| | - Betty Jo Salmeron
- Neuroimaging Research Branch, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, Maryland
| | - Amy C. Janes
- Neuroimaging Research Branch, National Institute on Drug Abuse Intramural Research Program, National Institutes of Health, Baltimore, Maryland
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8
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Jhaveri DJ, McGonigal A, Becker C, Benoliel JJ, Nandam LS, Soncin L, Kotwas I, Bernard C, Bartolomei F. Stress and Epilepsy: Towards Understanding of Neurobiological Mechanisms for Better Management. eNeuro 2023; 10:ENEURO.0200-23.2023. [PMID: 37923391 PMCID: PMC10626502 DOI: 10.1523/eneuro.0200-23.2023] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 09/03/2023] [Accepted: 09/20/2023] [Indexed: 11/07/2023] Open
Abstract
Stress has been identified as a major contributor to human disease and is postulated to play a substantial role in epileptogenesis. In a significant proportion of individuals with epilepsy, sensitivity to stressful events contributes to dynamic symptomatic burden, notably seizure occurrence and frequency, and presence and severity of psychiatric comorbidities [anxiety, depression, posttraumatic stress disorder (PTSD)]. Here, we review this complex relationship between stress and epilepsy using clinical data and highlight key neurobiological mechanisms including the hypothalamic-pituitary-adrenal (HPA) axis dysfunction, altered neuroplasticity within limbic system structures, and alterations in neurochemical pathways such as brain-derived neurotrophic factor (BNDF) linking epilepsy and stress. We discuss current clinical management approaches of stress that help optimize seizure control and prevention, as well as psychiatric comorbidities associated with epilepsy. We propose that various shared mechanisms of stress and epilepsy present multiple avenues for the development of new symptomatic and preventative treatments, including disease modifying therapies aimed at reducing epileptogenesis. This would require close collaborations between clinicians and basic scientists to integrate data across multiple scales, from genetics to systems biology, from clinical observations to fundamental mechanistic insights. In future, advances in machine learning approaches and neuromodulation strategies will enable personalized and targeted interventions to manage and ultimately treat stress-related epileptogenesis.
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Affiliation(s)
- Dhanisha J Jhaveri
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
- Mater Research Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Aileen McGonigal
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
- Mater Research Institute, Faculty of Medicine, The University of Queensland, Brisbane, QLD 4067, Australia
- Mater Epilepsy Unit, Department of Neurosciences, Mater Hospital, Brisbane, QLD 4101, Australia
| | - Christel Becker
- Institut National de la Santé et de la Recherche Médicale, Unité 1124, Université Paris Cité, Paris, 75006, France
| | - Jean-Jacques Benoliel
- Institut National de la Santé et de la Recherche Médicale, Unité 1124, Université Paris Cité, Paris, 75006, France
- Site Pitié-Salpêtrière, Service de Biochimie Endocrinienne et Oncologie, Assistance Publique Hôpitaux de Paris, Sorbonne Université, Paris, 75651, France
| | - L Sanjay Nandam
- Turner Inst for Brain & Mental Health, Faculty of Medicine, Nursing and Health Sciences, School of Psychological Sciences, Monash University, Melbourne, 3800, Australia
| | - Lisa Soncin
- Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes, Aix Marseille University, Marseille, 13005, France
- Laboratoire d'Anthropologie et de Psychologie Cliniques, Cognitives et Sociales, Côte d'Azur University, Nice, 06300, France
| | - Iliana Kotwas
- Epileptology and Cerebral Rhythmology, Assistance Publique Hôpitaux de Marseille, Timone Hospital, Marseille, 13005, France
| | - Christophe Bernard
- Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes, Aix Marseille University, Marseille, 13005, France
| | - Fabrice Bartolomei
- Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes, Aix Marseille University, Marseille, 13005, France
- Epileptology and Cerebral Rhythmology, Assistance Publique Hôpitaux de Marseille, Timone Hospital, Marseille, 13005, France
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Mao L, Wu Y, Hong X, Li P, Yuan X, Hu M. The influence of childhood maltreatment on trait depression in patients with major depressive disorder: A moderated mediation model of rumination and mindful attention awareness. J Affect Disord 2023; 331:130-138. [PMID: 36963511 DOI: 10.1016/j.jad.2023.03.052] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 03/06/2023] [Accepted: 03/18/2023] [Indexed: 03/26/2023]
Abstract
Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders. Individuals who were exposed to childhood maltreatment might be an especially vulnerable group and were more likely to meet the diagnostic criteria for depression than those who were not. Trait depression refers to a personality trait predisposition to depression, expressed as the frequency of symptoms rather than a transient depressive mood state. Clarifying the relationship between childhood maltreatment and trait depression in patients with MDD has therefore become an important field of research. Childhood Trauma Questionnaire-Short Form (CTQ-SF), Ruminative Responses Scale (RRS), State-Trait Depression Scale (ST-DEP), and Mindful Attention Awareness Scale (MAAS) were used as research instruments. SPSS 23.0 statistical software was used for statistical analysis and examined the moderated mediation models. A total of 288 patients with MDD were included in this study. After standardization of the variables, the model revealed childhood maltreatment was positively associated with trait depression (β = 0.215, p < 0.001) and that rumination partially mediated the effect between childhood trauma and trait depression. Mindfulness moderated the association between rumination and trait depression in depressed patients (β = 0.171, p < 0.001). Simple slope tests showed that rumination significantly predicted trait depression in patients with high levels of mindfulness (bsimple = 0.460, p < 0.001, 95%CI = [0.339, 0.581]), while this predictive effect was not significant in patients with low levels (bsimple = 0.119, p = 0.097, 95%CI = [-0.022, 0.261]). After adding mediating variables, we found that the negative impact of childhood maltreatment on trait depression was both directly and indirectly through the patients' own ruminative levels. However, mindfulness performed a critical moderating role in the overall mediating model, aggravating the negative impact of childhood maltreatment on trait depression. There are several limitations in this study: the history of childhood maltreatment was reviewed and reported; the MAAS was a single-dimensional questionnaire that fails to measure the content of other mindfulness factors; cross-sectional data could not be used to infer the causal relationship between variables.
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Affiliation(s)
- Lingyun Mao
- Department of Psychosomatic Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yunhong Wu
- Department of Psychosomatic Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xin Hong
- Department of Psychosomatic Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Pan Li
- Department of Psychosomatic Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xin Yuan
- Department of Psychosomatic Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Maorong Hu
- Department of Psychosomatic Medicine, The First Affiliated Hospital of Nanchang University, Nanchang, China.
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