1
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Branchi I. Uncovering the determinants of brain functioning, behavior and their interplay in the light of context. Eur J Neurosci 2024. [PMID: 38558227 DOI: 10.1111/ejn.16331] [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: 04/12/2023] [Accepted: 03/07/2024] [Indexed: 04/04/2024]
Abstract
Notwithstanding the huge progress in molecular and cellular neuroscience, our ability to understand the brain and develop effective treatments promoting mental health is still limited. This can be partially ascribed to the reductionist, deterministic and mechanistic approaches in neuroscience that struggle with the complexity of the central nervous system. Here, I introduce the Context theory of constrained systems proposing a novel role of contextual factors and genetic, molecular and neural substrates in determining brain functioning and behavior. This theory entails key conceptual implications. First, context is the main driver of behavior and mental states. Second, substrates, from genes to brain areas, have no direct causal link to complex behavioral responses as they can be combined in multiple ways to produce the same response and different responses can impinge on the same substrates. Third, context and biological substrates play distinct roles in determining behavior: context drives behavior, substrates constrain the behavioral repertoire that can be implemented. Fourth, since behavior is the interface between the central nervous system and the environment, it is a privileged level of control and orchestration of brain functioning. Such implications are illustrated through the Kitchen metaphor of the brain. This theoretical framework calls for the revision of key concepts in neuroscience and psychiatry, including causality, specificity and individuality. Moreover, at the clinical level, it proposes treatments inducing behavioral changes through contextual interventions as having the highest impact to reorganize the complexity of the human mind and to achieve a long-lasting improvement in mental health.
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Affiliation(s)
- Igor Branchi
- Center for Behavioral Sciences and Mental Health, Istituto Superiore di Sanità, Rome, Italy
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2
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Song EJ, Tozzi L, Williams LM. Brain Circuit-Derived Biotypes for Treatment Selection in Mood Disorders: A Critical Review and Illustration of a Functional Neuroimaging Tool for Clinical Translation. Biol Psychiatry 2024:S0006-3223(24)01175-2. [PMID: 38552866 DOI: 10.1016/j.biopsych.2024.03.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 03/16/2024] [Accepted: 03/20/2024] [Indexed: 05/12/2024]
Abstract
Although the lifetime burden due to major depressive disorder is increasing, we lack tools for selecting the most effective treatments for each patient. One-third to one-half of patients with major depressive disorder do not respond to treatment, and we lack strategies for selecting among available treatments or expediting access to new treatment options. This critical review concentrates on functional neuroimaging as a modality of measurement for precision psychiatry. We begin by summarizing the current landscape of how functional neuroimaging-derived circuit predictors can forecast treatment outcomes in depression. Then, we outline the opportunities and challenges in integrating circuit predictors into clinical practice. We highlight one standardized and reproducible approach for quantifying brain circuit function at an individual level, which could serve as a model for clinical translation. We conclude by evaluating the prospects and practicality of employing neuroimaging tools, such as the one that we propose, in routine clinical practice.
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Affiliation(s)
- Evelyn Jiayi Song
- Stanford Center for Precision Mental Health and Wellness, Psychiatry and Behavioral Sciences, Stanford, California; Stanford School of Engineering, Stanford, California
| | - Leonardo Tozzi
- Stanford Center for Precision Mental Health and Wellness, Psychiatry and Behavioral Sciences, Stanford, California
| | - Leanne M Williams
- Stanford Center for Precision Mental Health and Wellness, Psychiatry and Behavioral Sciences, Stanford, California; Mental Illness Research, Education and Clinical Center of Excellence (MIRECC), VA Palo Alto Health Care System, Palo Alto, California.
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3
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Babicola L, Mancini C, Riccelli C, Di Segni M, Passeri A, Municchi D, D'Addario SL, Andolina D, Cifani C, Cabib S, Ventura R. A mouse model of the 3-hit effects of stress: Genotype controls the effects of life adversities in females. Prog Neuropsychopharmacol Biol Psychiatry 2023; 127:110842. [PMID: 37611651 DOI: 10.1016/j.pnpbp.2023.110842] [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: 05/20/2023] [Revised: 08/14/2023] [Accepted: 08/17/2023] [Indexed: 08/25/2023]
Abstract
Helplessness is a dysfunctional coping response to stressors associated with different psychiatric conditions. The present study tested the hypothesis that early and adult adversities cumulate to produce helplessness depending on the genotype (3-hit hypothesis of psychopathology). To this aim, we evaluated whether Chronic Unpredictable Stress (CUS) differently affected coping and mesoaccumbens dopamine (DA) responses to stress challenge by adult mice of the C57BL/6J (B6) and DBA/2J (D2) inbred strains depending on early life experience (Repeated Cross Fostering, RCF). Three weeks of CUS increased the helplessness expressed in the Forced Swimming Test (FST) and the Tail Suspension Test by RCF-exposed female mice of the D2 strain. Moreover, female D2 mice with both RCF and CUS experiences showed inhibition of the stress-induced extracellular DA outflow in the Nucleus Accumbens, as measured by in vivo microdialysis, during and after FST. RCF-exposed B6 mice, instead, showed reduced helplessness and increased mesoaccumbens DA release. The present results support genotype-dependent additive effects of early experiences and adult adversities on behavioral and neural responses to stress by female mice. To our knowledge, this is the first report of a 3-hit effect in an animal model. Finally, the comparative analyses of behavioral and neural phenotypes expressed by B6 and D2 mice suggest some translationally relevant hypotheses of genetic risk factors for psychiatric disorders.
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Affiliation(s)
- Lucy Babicola
- IRCCS Fondazione Santa Lucia, Rome, Italy; Dept. of Psychology and Center "Daniel Bovet", Sapienza University, Rome 00184, Italy
| | - Camilla Mancini
- University of Camerino, School of Pharmacy, Pharmacology Unit, Camerino, Italy
| | - Cristina Riccelli
- Dept. of Psychology and Center "Daniel Bovet", Sapienza University, Rome 00184, Italy
| | - Matteo Di Segni
- IRCCS Fondazione Santa Lucia, Rome, Italy; Dept. of Psychology and Center "Daniel Bovet", Sapienza University, Rome 00184, Italy
| | - Alice Passeri
- Dept. of Psychology and Center "Daniel Bovet", Sapienza University, Rome 00184, Italy
| | - Diana Municchi
- IRCCS Fondazione Santa Lucia, Rome, Italy; Dept. of Psychology and Center "Daniel Bovet", Sapienza University, Rome 00184, Italy
| | | | - Diego Andolina
- IRCCS Fondazione Santa Lucia, Rome, Italy; Dept. of Psychology and Center "Daniel Bovet", Sapienza University, Rome 00184, Italy
| | - Carlo Cifani
- University of Camerino, School of Pharmacy, Pharmacology Unit, Camerino, Italy
| | - Simona Cabib
- IRCCS Fondazione Santa Lucia, Rome, Italy; Dept. of Psychology and Center "Daniel Bovet", Sapienza University, Rome 00184, Italy.
| | - Rossella Ventura
- IRCCS Fondazione Santa Lucia, Rome, Italy; IRCCS San Raffaele, Rome, Italy.
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4
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Schwartz EKC, Wolkowicz NR, De Aquino JP, MacLean RR, Sofuoglu M. Cocaine Use Disorder (CUD): Current Clinical Perspectives. Subst Abuse Rehabil 2022; 13:25-46. [PMID: 36093428 PMCID: PMC9451050 DOI: 10.2147/sar.s337338] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 08/22/2022] [Indexed: 11/29/2022] Open
Abstract
Cocaine use disorder (CUD) is a devastating disorder, impacting both individuals and society. Individuals with CUD face many barriers in accessing treatment for CUD, and most individuals with CUD never receive treatment. In this review, we provide an overview of CUD, including risk factors for CUD, common co-occurring disorders, acute and chronic effects of cocaine use, and currently available pharmacological and behavioral treatments. There are no FDA-approved pharmacological treatments for CUD. Future studies with larger sample sizes and testing treatment combinations are warranted. However, individuals with CUD and co-occurring disorders (eg, a mood or anxiety disorder) may benefit from medication treatments. There are behavioral interventions that have demonstrated efficacy in treating CUD – contingency management (CM) and cognitive-behavioral therapy for substance use disorders (CBT-SUD) in particular – however many barriers remain in delivering these treatments to patients. Following the discussion of current treatments, we highlight some promising emerging treatments, as well as offer a framework that can be used in building a treatment plan for individuals with CUD.
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Affiliation(s)
- Elizabeth K C Schwartz
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT, USA
- Correspondence: Elizabeth KC Schwartz, Tel +1-203-932-5711, Fax +1-203-937-3472, Email
| | - Noah R Wolkowicz
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT, USA
| | - Joao P De Aquino
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT, USA
| | - R Ross MacLean
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT, USA
| | - Mehmet Sofuoglu
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Department of Psychiatry, VA Connecticut Healthcare System, West Haven, CT, USA
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5
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Rutherford S, Kia SM, Wolfers T, Fraza C, Zabihi M, Dinga R, Berthet P, Worker A, Verdi S, Ruhe HG, Beckmann CF, Marquand AF. The normative modeling framework for computational psychiatry. Nat Protoc 2022; 17:1711-1734. [PMID: 35650452 PMCID: PMC7613648 DOI: 10.1038/s41596-022-00696-5] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 03/17/2022] [Indexed: 11/09/2022]
Abstract
Normative modeling is an emerging and innovative framework for mapping individual differences at the level of a single subject or observation in relation to a reference model. It involves charting centiles of variation across a population in terms of mappings between biology and behavior, which can then be used to make statistical inferences at the level of the individual. The fields of computational psychiatry and clinical neuroscience have been slow to transition away from patient versus 'healthy' control analytic approaches, probably owing to a lack of tools designed to properly model biological heterogeneity of mental disorders. Normative modeling provides a solution to address this issue and moves analysis away from case-control comparisons that rely on potentially noisy clinical labels. Here we define a standardized protocol to guide users through, from start to finish, normative modeling analysis using the Predictive Clinical Neuroscience toolkit (PCNtoolkit). We describe the input data selection process, provide intuition behind the various modeling choices and conclude by demonstrating several examples of downstream analyses that the normative model may facilitate, such as stratification of high-risk individuals, subtyping and behavioral predictive modeling. The protocol takes ~1-3 h to complete.
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Affiliation(s)
- Saige Rutherford
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands.
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands.
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
| | - Seyed Mostafa Kia
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Psychiatry, Utrecht University Medical Center, Utrecht, the Netherlands
| | - Thomas Wolfers
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research, University of Oslo, Oslo, Norway
| | - Charlotte Fraza
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Mariam Zabihi
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Richard Dinga
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Pierre Berthet
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research, University of Oslo, Oslo, Norway
| | - Amanda Worker
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Serena Verdi
- Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, University College London, London, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Henricus G Ruhe
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Christian F Beckmann
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
- Centre for Functional MRI of the Brain, University of Oxford, Oxford, UK
| | - Andre F Marquand
- Donders Institute for Brain, Cognition, and Behavior, Radboud University, Nijmegen, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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6
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Branchi I. Recentering neuroscience on behavior: The interface between brain and environment is a privileged level of control of neural activity. Neurosci Biobehav Rev 2022; 138:104678. [PMID: 35487322 DOI: 10.1016/j.neubiorev.2022.104678] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 04/21/2022] [Accepted: 04/22/2022] [Indexed: 02/08/2023]
Abstract
Despite the huge and constant progress in the molecular and cellular neuroscience fields, our capability to understand brain alterations and treat mental illness is still limited. Therefore, a paradigm shift able to overcome such limitation is warranted. Behavior and the associated mental states are the interface between the central nervous system and the living environment. Since, in any system, the interface is a key regulator of system organization, behavior is proposed here as a unique and privileged level of control and orchestration of brain structure and activity. This view has relevant scientific and clinical implications. First, the study of behavior represents a singular starting point for the investigation of neural activity in an integrated and comprehensive fashion. Second, behavioral changes, accomplished through psychotherapy or environmental interventions, are expected to have the highest impact to specifically reorganize the complexity of the human mind and thus achieve a solid and long-lasting improvement in mental health.
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Affiliation(s)
- Igor Branchi
- Center for Behavioral Sciences and Mental Health, Istituto Superiore di Sanità, Viale Regina Elena, 299, 00161 Rome, Italy.
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7
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Müller CP. Serotonin and Consciousness-A Reappraisal. Behav Brain Res 2022; 432:113970. [PMID: 35716774 DOI: 10.1016/j.bbr.2022.113970] [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: 03/18/2022] [Revised: 06/01/2022] [Accepted: 06/06/2022] [Indexed: 11/02/2022]
Abstract
The serotonergic system of the brain is a major modulator of behaviour. Here we describe a re-appraisal of its function for consciousness based on anatomical, functional and pharmacological data. For a better understanding, the current model of consciousness is expanded. Two parallel streams of conscious flow are distinguished. A flow of conscious content and an affective consciousness flow. While conscious content flow has its functional equivalent in the activity of higher cortico-cortical and cortico-thalamic networks, affective conscious flow originates in segregated deeper brain structures for single emotions. It is hypothesized that single emotional networks converge on serotonergic and other modulatory transmitter neurons in the brainstem where a bound percept of an affective conscious flow is formed. This is then dispersed to cortical and thalamic networks, where it is time locked with conscious content flow at the level of these networks. Serotonin acts in concert with other modulatory systems of the brain stem with some possible specialization on single emotions. Together, these systems signal a bound percept of affective conscious flow. Dysfunctions in the serotonergic system may not only give rise to behavioural and somatic symptoms, but also essentially affect the coupling of conscious affective flow with conscious content flow, leading to the affect-stained subjective side of mental disorders like anxiety, depression, or schizophrenia. The present model is an attempt to integrate the growing insights into serotonergic system function. However, it is acknowledged, that several key claims are still at a heuristic level that need further empirical support.
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Affiliation(s)
- Christian P Müller
- Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander-Universität Erlangen-Nürnberg, Schwabachanlage 6, 91054, Erlangen, Germany; Centre for Drug Research, Universiti Sains Malaysia, 11800 Minden, Penang, Malaysia.
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8
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Kabbara A, Robert G, Khalil M, Verin M, Benquet P, Hassan M. An electroencephalography connectome predictive model of major depressive disorder severity. Sci Rep 2022; 12:6816. [PMID: 35473962 PMCID: PMC9042869 DOI: 10.1038/s41598-022-10949-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 04/05/2022] [Indexed: 11/21/2022] Open
Abstract
Emerging evidence showed that major depressive disorder (MDD) is associated with disruptions of brain structural and functional networks, rather than impairment of isolated brain region. Thus, connectome-based models capable of predicting the depression severity at the individual level can be clinically useful. Here, we applied a machine-learning approach to predict the severity of depression using resting-state networks derived from source-reconstructed Electroencephalography (EEG) signals. Using regression models and three independent EEG datasets (N = 328), we tested whether resting state functional connectivity could predict individual depression score. On the first dataset, results showed that individuals scores could be reasonably predicted (r = 0.6, p = 4 × 10-18) using intrinsic functional connectivity in the EEG alpha band (8-13 Hz). In particular, the brain regions which contributed the most to the predictive network belong to the default mode network. We further tested the predictive potential of the established model by conducting two external validations on (N1 = 53, N2 = 154). Results showed statistically significant correlations between the predicted and the measured depression scale scores (r1 = 0.52, r2 = 0.44, p < 0.001). These findings lay the foundation for developing a generalizable and scientifically interpretable EEG network-based markers that can ultimately support clinicians in a biologically-based characterization of MDD.
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Affiliation(s)
- Aya Kabbara
- Lebanese Association for Scientific Research, Tripoli, Lebanon
- MINDig, F-35000, Rennes, France
| | - Gabriel Robert
- Academic Department of Psychiatry, Centre Hospitalier Guillaume Régnier, Rennes, France
- Empenn, U1228, IRISA, UMR 6074, Rennes, France
- Comportement et Noyaux Gris Centraux, EA 4712, CHU Rennes, Université de Rennes 1, 35000, Rennes, France
| | - Mohamad Khalil
- Azm Center for Research in Biotechnology and Its Applications, EDST, Tripoli, Lebanon
- CRSI Research Center, Faculty of Engineering, Lebanese University, Beirut, Lebanon
| | - Marc Verin
- Comportement et Noyaux Gris Centraux, EA 4712, CHU Rennes, Université de Rennes 1, 35000, Rennes, France
- Univ Rennes, Inserm, LTSI-U1099, F-35000, Rennes, France
| | - Pascal Benquet
- Univ Rennes, Inserm, LTSI-U1099, F-35000, Rennes, France
| | - Mahmoud Hassan
- MINDig, F-35000, Rennes, France.
- School of Science and Engineering, Reykjavik University, Reykjavik, Iceland.
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Mullarkey M, Dobias M, Sung J, Ahuvia I, Shumake J, Beevers C, Schleider J. Web-Based Single Session Intervention for Perceived Control Over Anxiety During COVID-19: Randomized Controlled Trial. JMIR Ment Health 2022; 9:e33473. [PMID: 35230962 PMCID: PMC9007232 DOI: 10.2196/33473] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 02/08/2022] [Accepted: 02/22/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Anxiety is rising across the United States during the COVID-19 pandemic, and social distancing mandates preclude in-person mental health care. Greater perceived control over anxiety has predicted decreased anxiety pathology, including adaptive responses to uncontrollable stressors. Evidence suggests that no-therapist, single-session interventions can strengthen perceived control over emotions like anxiety; similar programs, if designed for the COVID-19 context, could hold substantial public health value. OBJECTIVE Our registered report evaluated a no-therapist, single-session, online intervention targeting perceived control over anxiety in the COVID-19 context against a placebo intervention encouraging handwashing. We tested whether the intervention could (1) decrease generalized anxiety and increase perceived control over anxiety and (2) achieve this without decreasing social-distancing intentions. METHODS We tested these questions using a between-subjects design in a weighted-probability sample of US adults recruited via a closed online platform (ie, Prolific). All outcomes were indexed via online self-report questionnaires. RESULTS Of 522 randomized individuals, 500 (95.8%) completed the baseline survey and intervention. Intent-to-treat analyses using all randomized participants (N=522) found no support for therapeutic or iatrogenic effects; effects on generalized anxiety were d=-0.06 (95% CI -0.27 to 0.15; P=.48), effects on perceived control were d=0.04 (95% CI -0.08 to 0.16; P=.48), and effects on social-distancing intentions were d=-0.02 (95% CI -0.23 to 0.19; P=.83). CONCLUSIONS Strengths of this study included a large, nationally representative sample and adherence to open science practices. Implications for scalable interventions, including the challenge of targeting perceived control over anxiety, are discussed. TRIAL REGISTRATION ClinicalTrials.gov NCT04459455; https://clinicaltrials.gov/show/NCT04459455.
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Affiliation(s)
- Michael Mullarkey
- Department of Psychology, Stony Brook University, Stony Brook, NY, United States
| | - Mallory Dobias
- Department of Psychology, Stony Brook University, Stony Brook, NY, United States
| | - Jenna Sung
- Department of Psychology, Stony Brook University, Stony Brook, NY, United States
| | - Isaac Ahuvia
- Department of Psychology, Stony Brook University, Stony Brook, NY, United States
| | - Jason Shumake
- Department of Psychology, Stony Brook University, Stony Brook, NY, United States
| | - Christopher Beevers
- Department of Psychology, Stony Brook University, Stony Brook, NY, United States
| | - Jessica Schleider
- Department of Psychology, Stony Brook University, Stony Brook, NY, United States
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Cuthbert BN. Research Domain Criteria (RDoC): Progress and Potential. CURRENT DIRECTIONS IN PSYCHOLOGICAL SCIENCE 2022; 31:107-114. [PMID: 35692384 PMCID: PMC9187047 DOI: 10.1177/09637214211051363] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/27/2023]
Abstract
The National Institute of Mental Health (NIMH) addressed in its 2008 Strategic Plan an emerging concern that the current diagnostic system was hampering translational research, as accumulating data suggested that disorder categories constituted heterogeneous syndromes rather than specific diseases. However, established practices in peer review placed high priority on extant disorders in evaluating grant applications for mental illness. To provide guidelines for alternative study designs, NIMH included a goal to develop new ways of studying psychopathology based on dimensions of measurable behavior and related neurobiological measures. The Research Domain Criteria (RDoC) project is the result, intended to build a literature that informs new conceptions of mental illness and future revisions to diagnostic manuals. The framework calls for the study of empirically-derived fundamental dimensions as characterized by related behavioral/psychological and neurobiological data (e.g., reward valuation, working memory). RDoC also emphasizes full-range dimensional approaches (from typical to increasingly abnormal), neurodevelopment and environmental effects, and research designs that integrate data across behavioral, biological, and self-report measures. This commentary provides an overview of the project's first decade and its potential future directions. RDoC remains grounded in experimental psychopathology perspectives, and its progress is strongly linked to psychological measurement and integrative approaches to brain-behavior relationships.
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11
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Petrolini V, Vicente A. The challenges raised by comorbidity in psychiatric research: The case of autism. PHILOSOPHICAL PSYCHOLOGY 2022. [DOI: 10.1080/09515089.2022.2052829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Valentina Petrolini
- Department of Linguistics and Basque Studies, Centro de Investigación Micaela Portilla, University of the Basque Country- UPV/EHU, Vitoria-Gasteiz, Spain
| | - Agustín Vicente
- Ikerbasque Foundation of Science/ Department of Linguistics and Basque Studies, Centro de Investigación Micaela Portilla, Ikerbasque Foundation of Science/University of the Basque Country - UPV/EHU, Vitoria-Gasteiz, Spain
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12
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Singla RK, Joon S, Shen L, Shen B. Translational Informatics for Natural Products as Antidepressant Agents. Front Cell Dev Biol 2022; 9:738838. [PMID: 35127696 PMCID: PMC8811306 DOI: 10.3389/fcell.2021.738838] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 12/13/2021] [Indexed: 12/18/2022] Open
Abstract
Depression, a neurological disorder, is a universally common and debilitating illness where social and economic issues could also become one of its etiologic factors. From a global perspective, it is the fourth leading cause of long-term disability in human beings. For centuries, natural products have proven their true potential to combat various diseases and disorders, including depression and its associated ailments. Translational informatics applies informatics models at molecular, imaging, individual, and population levels to promote the translation of basic research to clinical applications. The present review summarizes natural-antidepressant-based translational informatics studies and addresses challenges and opportunities for future research in the field.
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Affiliation(s)
- Rajeev K. Singla
- Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
- iGlobal Research and Publishing Foundation, New Delhi, India
| | - Shikha Joon
- Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
- iGlobal Research and Publishing Foundation, New Delhi, India
| | - Li Shen
- Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
| | - Bairong Shen
- Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China
- *Correspondence: Bairong Shen,
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Mondelli V, Cattaneo A, Nikkheslat N, Souza L, Walsh A, Zajkowska Z, Zonca V, Marizzoni M, Fisher HL, Kohrt BA, Kieling C, Di Meglio P. Exploring the role of immune pathways in the risk and development of depression in adolescence: Research protocol of the IDEA-FLAME study. Brain Behav Immun Health 2021; 18:100396. [PMID: 34927102 PMCID: PMC8648954 DOI: 10.1016/j.bbih.2021.100396] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 11/23/2021] [Accepted: 11/23/2021] [Indexed: 10/29/2022] Open
Abstract
Extensive research suggests a role for the innate immune system in the pathogenesis of depression, but most of the studies are conducted in adult populations, in high-income countries and mainly focus on the study of inflammatory proteins alone, which provides only a limited understanding of the immune pathways involved in the development of depression. The IDEA-FLAME study aims to identify immune phenotypes underlying increased risk of developing depression in adolescence in a middle-income country. To this end, we will perform deep-immunophenotyping of peripheral blood mononuclear cells and RNA genome-wide gene expression analyses in a longitudinal cohort of Brazilian adolescents stratified for depression risk. The project will involve the 3-year follow-up of an already recruited cohort of 150 Brazilian adolescents selected for risk/presence of depression on the basis of a composite risk score we developed using sociodemographic characteristics (50 adolescents with low-risk and 50 with high-risk of developing depression, and 50 adolescents with a current major depressive disorder). We will 1) test whether the risk group classification at baseline is associated with differences in immune cell frequency, phenotype and functional status, 2) test whether baseline immune markers (cytokines and immune cell markers) are associated with severity of depression at 3-year follow-up, and 3) identify changes in gene expression of immune pathways over the 3-year follow-up in adolescents with increased risk and presence of depression. Because of the exploratory nature of the study, the findings would need to be replicated in a separate and larger sample. Ultimately, this research will contribute to elucidating key immune therapeutic targets and inform the development of interventions to prevent onset of depression among adolescents.
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Affiliation(s)
- Valeria Mondelli
- King's College London, Department of Psychological Medicine, Institute of Psychiatry, Psychology, London, UK.,National Institute for Health Research Mental Health Biomedical Research Centre, South London and Maudsley NHS Foundation Trust and King's College London, London, UK
| | - Annamaria Cattaneo
- Department of Pharmacological and Biomolecular Sciences, University of Milan, Via Balzaretti 9, 20133, Milan, Italy.,Laboratory of Biological Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Naghmeh Nikkheslat
- King's College London, Department of Psychological Medicine, Institute of Psychiatry, Psychology, London, UK
| | - Laila Souza
- Departamento de Psiquiatria, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Annabel Walsh
- King's College London, Department of Psychological Medicine, Institute of Psychiatry, Psychology, London, UK
| | - Zuzanna Zajkowska
- King's College London, Department of Psychological Medicine, Institute of Psychiatry, Psychology, London, UK
| | - Valentina Zonca
- King's College London, Department of Psychological Medicine, Institute of Psychiatry, Psychology, London, UK.,Laboratory of Biological Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Moira Marizzoni
- Laboratory of Biological Psychiatry, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Helen L Fisher
- King's College London, Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, London, UK.,ESRC Centre for Society and Mental Health, King's College London, London, UK
| | - Brandon A Kohrt
- Division of Global Mental Health, Department of Psychiatry, School of Medicine and Health Sciences, The George Washington University, Washington, DC, USA
| | - Christian Kieling
- Departamento de Psiquiatria, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,Serviço de Psiquiatria da Infância e Adolescência, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil
| | - Paola Di Meglio
- St John's Institute of Dermatology, King's College London, London, UK.,National Institute for Health Research Mental Health Biomedical Research Centre, Guy's and St Thomas' NHS Foundation Trust and King's College London, London, UK
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14
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Examining Relations Between Obsessive-Compulsive Features, Substance-Use Disorders, and Antisocial Personality Disorder in the Vietnam Era Twin Cohort. Int J Ment Health Addict 2021. [DOI: 10.1007/s11469-020-00299-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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15
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Perugi G, Barbuti M. There are no patients without comorbidity. Eur Neuropsychopharmacol 2021; 50:104-106. [PMID: 34077858 DOI: 10.1016/j.euroneuro.2021.05.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 05/04/2021] [Accepted: 05/06/2021] [Indexed: 11/24/2022]
Affiliation(s)
- Giulio Perugi
- Department of Clinical and Experimental Medicine, University of Pisa, Via Savi 10, Pisa 56126, Italy; U.O. Psichiatria 2, Azienda Ospedaliera Universitaria Pisana (AOUP), Pisa, Italy.
| | - Margherita Barbuti
- Department of Clinical and Experimental Medicine, University of Pisa, Via Savi 10, Pisa 56126, Italy
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16
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Rutherford S, Kia SM, Wolfers T, Fraza C, Zabihi M, Dinga R, Berthet P, Worker A, Verdi S, Ruhe HG, Beckmann CF, Marquand AF. The Normative Modeling Framework for Computational Psychiatry.. [PMID: 35650452 PMCID: PMC7613648 DOI: 10.1101/2021.08.08.455583] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Normative modeling is an emerging and innovative framework for mapping individual differences at the level of a single subject or observation in relation to a reference model. It involves charting centiles of variation across a population in terms of mappings between biology and behavior which can then be used to make statistical inferences at the level of the individual. The fields of computational psychiatry and clinical neuroscience have been slow to transition away from patient versus “healthy” control analytic approaches, likely due to a lack of tools designed to properly model biological heterogeneity of mental disorders. Normative modeling provides a solution to address this issue and moves analysis away from case-control comparisons that rely on potentially noisy clinical labels. In this article, we define a standardized protocol to guide users through, from start to finish, normative modeling analysis using the Predictive Clinical Neuroscience toolkit (PCNtoolkit). We describe the input data selection process, provide intuition behind the various modeling choices, and conclude by demonstrating several examples of down-stream analyses the normative model results may facilitate, such as stratification of high-risk individuals, subtyping, and behavioral predictive modeling. The protocol takes approximately 1-3 hours to complete.
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17
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Yao Y, Stephan KE. Markov chain Monte Carlo methods for hierarchical clustering of dynamic causal models. Hum Brain Mapp 2021; 42:2973-2989. [PMID: 33826194 PMCID: PMC8193526 DOI: 10.1002/hbm.25431] [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: 12/14/2020] [Revised: 03/15/2021] [Accepted: 03/18/2021] [Indexed: 01/14/2023] Open
Abstract
In this article, we address technical difficulties that arise when applying Markov chain Monte Carlo (MCMC) to hierarchical models designed to perform clustering in the space of latent parameters of subject‐wise generative models. Specifically, we focus on the case where the subject‐wise generative model is a dynamic causal model (DCM) for functional magnetic resonance imaging (fMRI) and clusters are defined in terms of effective brain connectivity. While an attractive approach for detecting mechanistically interpretable subgroups in heterogeneous populations, inverting such a hierarchical model represents a particularly challenging case, since DCM is often characterized by high posterior correlations between its parameters. In this context, standard MCMC schemes exhibit poor performance and extremely slow convergence. In this article, we investigate the properties of hierarchical clustering which lead to the observed failure of standard MCMC schemes and propose a solution designed to improve convergence but preserve computational complexity. Specifically, we introduce a class of proposal distributions which aims to capture the interdependencies between the parameters of the clustering and subject‐wise generative models and helps to reduce random walk behaviour of the MCMC scheme. Critically, these proposal distributions only introduce a single hyperparameter that needs to be tuned to achieve good performance. For validation, we apply our proposed solution to synthetic and real‐world datasets and also compare it, in terms of computational complexity and performance, to Hamiltonian Monte Carlo (HMC), a state‐of‐the‐art Monte Carlo technique. Our results indicate that, for the specific application domain considered here, our proposed solution shows good convergence performance and superior runtime compared to HMC.
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Affiliation(s)
- Yu Yao
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Klaas E Stephan
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland.,Max Planck Institute for Metabolism Research, Cologne, Germany
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18
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Chestnykh DA, Amato D, Kornhuber J, Müller CP. Pharmacotherapy of schizophrenia: Mechanisms of antipsychotic accumulation, therapeutic action and failure. Behav Brain Res 2021; 403:113144. [PMID: 33515642 DOI: 10.1016/j.bbr.2021.113144] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 01/21/2021] [Accepted: 01/22/2021] [Indexed: 12/13/2022]
Abstract
Schizophrenia is a multi-dimensional disorder with a complex and mostly unknown etiology, leading to a severe decline in life quality. Antipsychotic drugs (APDs) remain beneficial interventions in the treatment of the disorder, but vary significantly in binding profile, clinical effects and adverse reactions. The present review summarizes the main principles of APD mechanisms of action with a particular focus on recent findings in APD accumulation and its role in the therapeutic efficacy and treatment failure. High and low doses of APDs were shown to be effective in different dimensions of antipsychotic-like behaviour in rodent models. Efficacy of the APDs correlates with high dopamine D2 receptor occupancy, which occurs quickly after drug administration. However, onset and peak of action are delayed up to several days or weeks. APD accumulation via acidic trapping in synaptic vesicles is considered to underlie the time course of APD action. Use-dependent exocytosis, co-release with dopamine and serotonin and inhibition of ion channels impact on the neuronal transmission and determine effects of APDs. Disruption in accumulating properties leads to diminished APD effects. In addition, long-term APD administration at therapeutic doses leads to treatment failure both in animal models and in humans. APD failure was associated with treatment induced neuroadaptations, including a decline in extracellular dopamine levels, dopamine transporter upregulation, and altered neuronal firing. However, enhanced synaptic vesicle release has also been reported. APD loss of efficacy may be reversed through inhibition of the dopamine transporter or switching the administration regimen from continuous to intermittent. Thus, manipulating the accumulation properties of APDs, changes in the administration regimen and doses, or co-administration with dopamine transporter inhibitors may be considered to yield benefits in the development of new effective strategies in the treatment of schizophrenia.
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Affiliation(s)
- Daria A Chestnykh
- Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054, Erlangen, Germany
| | - Davide Amato
- Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054, Erlangen, Germany; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054, Erlangen, Germany
| | - Christian P Müller
- Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054, Erlangen, Germany.
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19
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The Need of Personalized Medicine in Coping with Stress during Infertility Treatment. J Pers Med 2021; 11:jpm11010056. [PMID: 33477431 PMCID: PMC7830688 DOI: 10.3390/jpm11010056] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 12/09/2020] [Accepted: 01/15/2021] [Indexed: 12/20/2022] Open
Abstract
The term personalized medicine was created for oncological patients, but due to its positive clinical results it is now used in many other fields of medicine, including reproductive medicine. The aim of the study was to determine the level of stress and strategies of coping with stress in patients treated for infertility. The study—using a questionnaire developed by the authors, the Perceived Stress Scale-10 (PSS-10), and the Coping Orientation to Problems Experienced Inventory (Mini-COPE)—was conducted among 456 people from infertile couples. Conclusions: More than half of the studied patients demonstrated a high level of stress. The choice of coping strategies was related to the respondents’ gender and level of stress as well as their experience with assisted reproductive technology.
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20
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Neutral sphingomyelinase mediates the co-morbidity trias of alcohol abuse, major depression and bone defects. Mol Psychiatry 2021; 26:7403-7416. [PMID: 34584229 PMCID: PMC8872992 DOI: 10.1038/s41380-021-01304-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 09/06/2021] [Accepted: 09/09/2021] [Indexed: 02/07/2023]
Abstract
Mental disorders are highly comorbid and occur together with physical diseases, which are often considered to arise from separate pathogenic pathways. We observed in alcohol-dependent patients increased serum activity of neutral sphingomyelinase. A genetic association analysis in 456,693 volunteers found associations of haplotypes of SMPD3 coding for NSM-2 (NSM) with alcohol consumption, but also with affective state, and bone mineralisation. Functional analysis in mice showed that NSM controls alcohol consumption, affective behaviour, and their interaction by regulating hippocampal volume, cortical connectivity, and monoaminergic responses. Furthermore, NSM controlled bone-brain communication by enhancing osteocalcin signalling, which can independently supress alcohol consumption and reduce depressive behaviour. Altogether, we identified a single gene source for multiple pathways originating in the brain and bone, which interlink disorders of a mental-physical co-morbidity trias of alcohol abuse-depression/anxiety-bone disorder. Targeting NSM and osteocalcin signalling may, thus, provide a new systems approach in the treatment of a mental-physical co-morbidity trias.
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21
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Coledam DHC, Silva YMD. Prescribed medication use among elementary teachers: Prevalence and associated factors. CIENCIA & SAUDE COLETIVA 2020; 25:5051-5064. [PMID: 33295522 DOI: 10.1590/1413-812320202512.20912018] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2018] [Accepted: 04/15/2019] [Indexed: 11/21/2022] Open
Abstract
The aims of the study were to assess the prevalence and analyze the associated factors of medication use among teachers. A cross-sectional study was carried out, involving 530 teachers from Londrina city, Paraná, Brazil. The dependent variable was prescribed medication use and the independent variables were sociodemographic, work-related, lifestyle, health disorders, and chronic diseases, all assessed through questionnaires. Prevalence of medication use was 59.1%. Chronic disease was associated with all medications analyzed. Variables positively associated with medication use according to health disorder type were: Cardiometabolic (Length of employment, overweight, not current tobacco use, and TV viewing); Psychological (Length of employment, common mental disorders, current tobacco use, and disability); Orthopedic (Length of employment, health insurance, overweight, musculoskeletal pain, low job support, and disability); Respiratory (TV viewing and problems related to dust or chalk powder); and Gastrointestinal (common mental disorders and physical activity [negative association]). Support for access, the appropriate use of medicines, and a reduction in medication use should consider work-related, lifestyle, and health disorders, as well as chronic diseases.
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Affiliation(s)
- Diogo Henrique Constantino Coledam
- Instituto Federal de Educação, Ciência e Tecnologia de São Paulo. Av. Zélia de Lima Rosa 100, Portal dos Pássaros. 18550-000 Boituva SP Brasil.
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22
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Scott J, Colom F, Young A, Bellivier F, Etain B. An evidence map of actigraphy studies exploring longitudinal associations between rest-activity rhythms and course and outcome of bipolar disorders. Int J Bipolar Disord 2020; 8:37. [PMID: 33258017 PMCID: PMC7704984 DOI: 10.1186/s40345-020-00200-6] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 08/25/2020] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Evidence mapping is a structured approach used to synthesize the state-of-the-art in an emerging field of research when systematic reviews or meta-analyses are deemed inappropriate. We employed this strategy to summarise knowledge regarding longitudinal ecological monitoring of rest-activity rhythms (RAR) and disease modifiers, course of illness, treatment response or outcome in bipolar disorders (BD). STRUCTURE We had two key aims: (1) to determine the number and type of actigraphy studies of in BD that explored data regarding: outcome over time (e.g. relapse/recurrence according to polarity, or recovery/remission), treatment response or illness trajectories and (2) to examine the range of actigraphy metrics that can be used to estimate disruptions of RAR and describe which individual circadian rhythm or sleep-wake cycle parameters are most consistently associated with outcome over time in BD. The mapping process incorporated four steps: clarifying the project focus, describing boundaries and 'coordinates' for mapping, searching the literature and producing a brief synopsis with summary charts of the key outputs. Twenty-seven independent studies (reported in 29 publications) were eligible for inclusion in the map. Most were small-scale, with the median sample size being 15 per study and median duration of actigraphy being about 7 days (range 1-210). Interestingly, 17 studies comprised wholly or partly of inpatients (63%). The available evidence indicated that a discrete number of RAR metrics are more consistently associated with transition between different phases of BD and/or may be predictive of longitudinal course of illness or treatment response. The metrics that show the most frequent associations represent markers of the amount, timing, or variability of RAR rather than the sleep quality metrics that are frequently targeted in contemporary studies of BD. CONCLUSIONS Despite 50 years of research, use of actigraphy to assess RAR in longitudinal studies and examination of these metrics and treatment response, course and outcome of BD is under-investigated. This is in marked contrast to the extensive literature on case-control or cross-sectional studies of actigraphy, especially typical sleep analysis metrics in BD. However, given the encouraging findings on putative RAR markers, we recommend increased study of putative circadian phenotypes of BD.
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Affiliation(s)
- Jan Scott
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- Université Paris Diderot, Sorbonne Paris Cité, UMR-S 1144, 75013, Paris, France
| | - Francesc Colom
- IMIM-Hospital del Mar-CIBERSAM, Barcelona, Catalonia, Spain
- Universitat Autònoma de Barcelona Barcelona-Catalonia, Barcelona, Spain
| | - Allan Young
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- South London and Maudsley NHS Foundation Trust, Bethlem Royal Hospital, Kent, UK
| | - Frank Bellivier
- Université Paris Diderot, Sorbonne Paris Cité, UMR-S 1144, 75013, Paris, France
- Département de Psychiatrie Et de Médecine Addictologique, AP-HP, GH Saint-Louis - Lariboisière - F. Widal, 75475, Paris, France
- Inserm U114475006, Paris, France
| | - Bruno Etain
- Université Paris Diderot, Sorbonne Paris Cité, UMR-S 1144, 75013, Paris, France.
- Département de Psychiatrie Et de Médecine Addictologique, AP-HP, GH Saint-Louis - Lariboisière - F. Widal, 75475, Paris, France.
- Inserm U114475006, Paris, France.
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23
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Gauld C, Dumas G, Darrason M, Salles N, Desvergnes P, Philip P, Micoulaud-Franchi JA. Médecine du sommeil personnalisée et syndrome d’apnées hypopnées obstructives du sommeil : entre précision et stratification, une proposition de clarification. ACTA ACUST UNITED AC 2020. [DOI: 10.1016/j.msom.2020.08.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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24
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Schneider M, Elbau IG, Nantawisarakul T, Pöhlchen D, Brückl T, BeCOME Working Group, Czisch M, Saemann PG, Lee MD, Binder EB, Spoormaker VI. Pupil Dilation during Reward Anticipation Is Correlated to Depressive Symptom Load in Patients with Major Depressive Disorder. Brain Sci 2020; 10:E906. [PMID: 33255604 PMCID: PMC7760331 DOI: 10.3390/brainsci10120906] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 11/17/2020] [Accepted: 11/21/2020] [Indexed: 12/18/2022] Open
Abstract
Depression is a debilitating disorder with high prevalence and socioeconomic cost, but the brain-physiological processes that are altered during depressive states are not well understood. Here, we build on recent findings in macaques that indicate a direct causal relationship between pupil dilation and anterior cingulate cortex mediated arousal during anticipation of reward. We translated these findings to human subjects with concomitant pupillometry/fMRI in a sample of unmedicated participants diagnosed with major depression and healthy controls. We could show that the upregulation and maintenance of arousal in anticipation of reward was disrupted in patients in a symptom-load dependent manner. We could further show that the failure to maintain reward anticipatory arousal showed state-marker properties, as it tracked the load and impact of depressive symptoms independent of prior diagnosis status. Further, group differences of anticipatory arousal and continuous correlations with symptom load were not traceable only at the level of pupillometric responses, but were mirrored also at the neural level within salience network hubs. The upregulation and maintenance of arousal during reward anticipation is a novel translational and well-traceable process that could prove a promising gateway to a physiologically informed patient stratification and targeted interventions.
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Affiliation(s)
- Max Schneider
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany; (M.S.); (I.G.E.); (T.N.); (D.P.); (T.B.); (BeCOME Working Group); (M.C.); (P.G.S.); (E.B.B.)
| | - Immanuel G. Elbau
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany; (M.S.); (I.G.E.); (T.N.); (D.P.); (T.B.); (BeCOME Working Group); (M.C.); (P.G.S.); (E.B.B.)
| | - Teachawidd Nantawisarakul
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany; (M.S.); (I.G.E.); (T.N.); (D.P.); (T.B.); (BeCOME Working Group); (M.C.); (P.G.S.); (E.B.B.)
| | - Dorothee Pöhlchen
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany; (M.S.); (I.G.E.); (T.N.); (D.P.); (T.B.); (BeCOME Working Group); (M.C.); (P.G.S.); (E.B.B.)
| | - Tanja Brückl
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany; (M.S.); (I.G.E.); (T.N.); (D.P.); (T.B.); (BeCOME Working Group); (M.C.); (P.G.S.); (E.B.B.)
| | - BeCOME Working Group
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany; (M.S.); (I.G.E.); (T.N.); (D.P.); (T.B.); (BeCOME Working Group); (M.C.); (P.G.S.); (E.B.B.)
| | - Michael Czisch
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany; (M.S.); (I.G.E.); (T.N.); (D.P.); (T.B.); (BeCOME Working Group); (M.C.); (P.G.S.); (E.B.B.)
| | - Philipp G. Saemann
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany; (M.S.); (I.G.E.); (T.N.); (D.P.); (T.B.); (BeCOME Working Group); (M.C.); (P.G.S.); (E.B.B.)
| | - Michael D. Lee
- Department of Cognitive Sciences, University of California, Irvine, CA 92697-5100, USA;
| | - Elisabeth B. Binder
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany; (M.S.); (I.G.E.); (T.N.); (D.P.); (T.B.); (BeCOME Working Group); (M.C.); (P.G.S.); (E.B.B.)
| | - Victor I. Spoormaker
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, 80804 Munich, Germany; (M.S.); (I.G.E.); (T.N.); (D.P.); (T.B.); (BeCOME Working Group); (M.C.); (P.G.S.); (E.B.B.)
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25
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Kopf-Beck J, Zimmermann P, Egli S, Rein M, Kappelmann N, Fietz J, Tamm J, Rek K, Lucae S, Brem AK, Sämann P, Schilbach L, Keck ME. Schema therapy versus cognitive behavioral therapy versus individual supportive therapy for depression in an inpatient and day clinic setting: study protocol of the OPTIMA-RCT. BMC Psychiatry 2020; 20:506. [PMID: 33054737 PMCID: PMC7557007 DOI: 10.1186/s12888-020-02880-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 09/19/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Major depressive disorder represents (MDD) a major cause of disability and disease burden. Beside antidepressant medication, psychotherapy is a key approach of treatment. Schema therapy has been shown to be effective in the treatment of psychiatric disorders, especially personality disorders, in a variety of settings and patient groups. Nevertheless, there is no evidence on its effectiveness for MDD in an inpatient nor day clinic setting and little is known about the factors that drive treatment response in such a target group. METHODS In the current protocol, we outline OPTIMA (OPtimized Treatment Identification at the MAx Planck Institute): a single-center randomized controlled trial of schema therapy as a treatment approach for MDD in an inpatient and day clinic setting. Over the course of 7 weeks, we compare schema therapy with cognitive behavioral therapy and individual supportive therapy, conducted in individual and group sessions and with no restrictions regarding concurrent antidepressant medication, thus approximating real-life treatment conditions. N = 300 depressed patients are included. All study therapists undergo a specific training and supervision and therapy adherence is assessed. Primary outcome is depressive symptom severity as self-assessment (Beck Depression Inventory-II) and secondary outcomes are clinical ratings of MDD (Montgomery-Asberg Depression Rating Scale), recovery rates after 7 weeks according to the Munich-Composite International Diagnostic Interview, general psychopathology (Brief Symptom Inventory), global functioning (World Health Organization Disability Assessment Schedule), and clinical parameters such as dropout rates. Further parameters on a behavioral, cognitive, psychophysiological, and biological level are measured before, during and after treatment and in 2 follow-up assessments after 6 and 24 months after end of treatment. DISCUSSION To our knowledge, the OPTIMA-Trial is the first to investigate the effectiveness of schema therapy as a treatment approach of MDD, to investigate mechanisms of change, and explore predictors of treatment response in an inpatient and day clinic setting by using such a wide range of parameters. Insights from OPTIMA will allow more integrative approaches of psychotherapy of MDD. Especially, the identification of intervention-specific markers of treatment response can improve evidence-based clinical decision for individualizing treatment. TRIAL REGISTRATION Identifier on clinicaltrials.gov : NCT03287362 ; September, 12, 2017.
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Affiliation(s)
- Johannes Kopf-Beck
- Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804, Munich, Germany.
| | - Petra Zimmermann
- Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804, Munich, Germany
| | - Samy Egli
- Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804, Munich, Germany
| | - Martin Rein
- Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804, Munich, Germany
| | - Nils Kappelmann
- Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804, Munich, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
| | - Julia Fietz
- Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804, Munich, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
| | - Jeanette Tamm
- Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804, Munich, Germany
| | - Katharina Rek
- Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804, Munich, Germany
- University of Kassel, Kassel, Germany
| | - Susanne Lucae
- Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804, Munich, Germany
| | - Anna-Katharine Brem
- Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804, Munich, Germany
- Berenson-Allen Center for Noninvasive Brain Stimulation, Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- University Hospital of Old Age Psychiatry, University of Bern, Bern, Switzerland
- Department of Neuropsychology, Lucerne Psychiatry, Lucerne, Switzerland
| | - Philipp Sämann
- Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804, Munich, Germany
| | - Leonhard Schilbach
- Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804, Munich, Germany
- Independent Max Planck Research Group for Social Neuroscience, München, Germany
- Ludwig-Maximilians-Universität, Munich, Germany
| | - Martin E Keck
- Max Planck Institute of Psychiatry, Kraepelinstraße 2-10, 80804, Munich, Germany
- Schmieder Hospital in Gailingen, Gailingen, Germany
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Schraut KG, Kalnytska O, Lamp D, Jastroch M, Eder M, Hausch F, Gassen NC, Moore S, Nagaraj N, Lopez JP, Chen A, Schmidt MV. Loss of the psychiatric risk factor SLC6A15 is associated with increased metabolic functions in primary hippocampal neurons. Eur J Neurosci 2020; 53:390-401. [PMID: 33007132 DOI: 10.1111/ejn.14990] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 08/25/2020] [Accepted: 09/22/2020] [Indexed: 11/30/2022]
Abstract
Major depressive disorder (MDD) is one of the most severe global health problems with millions of people affected, however, the mechanisms underlying this disorder is still poorly understood. Genome-wide association studies have highlighted a link between the neutral amino acid transporter SLC6A15 and MDD. Additionally, a number of preclinical studies support the function of this transporter in modulating levels of brain neurotransmitters, stress system regulation and behavioural phenotypes related to MDD. However, the molecular and functional mechanisms involved in this interaction are still unresolved. Therefore, to investigate the effects of the SLC6A15 transporter, we used hippocampal tissue from Slc6a15-KO and wild-type mice, together with several in-vitro assays in primary hippocampal neurons. Utilizing a proteomics approach we identified differentially regulated proteins that formed a regulatory network and pathway analysis indicated significantly affected cellular domains, including metabolic, mitochondrial and structural functions. Furthermore, we observed reduced release probability at glutamatergic synapses, increased mitochondrial function, higher GSH/GSSG redox ratio and an improved neurite outgrowth in primary neurons lacking SLC6A15. In summary, we hypothesize that by controlling the intracellular concentrations of neutral amino acids, SLC6A15 affects mitochondrial activity, which could lead to alterations in neuronal structure and activity. These data provide further indication that a pharmacological or genetic reduction of SLC6A15 activity may indeed be a promising approach for antidepressant therapy.
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Affiliation(s)
- Karla-Gerlinde Schraut
- Research Group Neurobiology of Stress Resilience, Max Planck Institute of Psychiatry, Munich, Germany
| | - Oleksandra Kalnytska
- Research Group Neurobiology of Stress Resilience, Max Planck Institute of Psychiatry, Munich, Germany
| | - Daniel Lamp
- Institute for Diabetes and Obesity, Helmholtz Zentrum München, Neuherberg, Germany
| | - Martin Jastroch
- Institute for Diabetes and Obesity, Helmholtz Zentrum München, Neuherberg, Germany
| | - Matthias Eder
- Department Stress Neurobiology and Neurogenetics, Max Planck Institute of Psychiatry, Munich, Germany
| | - Felix Hausch
- Structure-Based Drug Research, Technische Universität Darmstadt, Darmstadt, Germany
| | - Nils C Gassen
- Department of Psychiatry and Psychotherapy, Bonn Clinical Center, University of Bonn, Bonn, Germany
| | - Sarah Moore
- Department of Medical Genetics, University of British Columbia, BC Children's Hospital Research Institute, Vancouver, Canada.,Department Translational Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Nagarjuna Nagaraj
- Biochemistry Core Facility, Max Planck Institute of Biochemistry, Munich, Germany
| | - Juan P Lopez
- Department Stress Neurobiology and Neurogenetics, Max Planck Institute of Psychiatry, Munich, Germany
| | - Alon Chen
- Department Stress Neurobiology and Neurogenetics, Max Planck Institute of Psychiatry, Munich, Germany
| | - Mathias V Schmidt
- Research Group Neurobiology of Stress Resilience, Max Planck Institute of Psychiatry, Munich, Germany
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27
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Severity of self-reported depressive symptoms in a healthy sample is modulated by trait Harm Avoidance, not by 5-HTTLPR polymorphism. Psychiatry Res 2020; 291:113029. [PMID: 32619821 DOI: 10.1016/j.psychres.2020.113029] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Accepted: 04/19/2020] [Indexed: 01/21/2023]
Abstract
BACKGROUND The length of the serotonin transporter polymorphic region (5-HTTLPR) has been suggested to be associated with risk for developing depression, though with inconsistent evidence. Likewise, the personality trait Harm Avoidance (HA) has been linked to vulnerability for developing depression. However, no study has investigated whether there is an interaction effect between 5-HTTLPR and trait HA on depressive symptoms in healthy individuals. METHODS A total of 319 healthy individuals were included in this cross-sectional study. All participants were genotyped for the 5-HTTLPR polymorphism and completed self-reported measures of personality trait HA with the Temperament and Character Inventory (TCI), and of depression with the Major Depression Inventory (MDI). Linear regression analyses were used to test interaction effects between 5-HTTLPR and HA on MDI. Post hoc analyses were further performed to investigate main effects of HA and possible interaction effects between 5-HTTLPR and HA sub-scales on MDI. RESULTS No significant interaction effect between 5-HTTLPR and HA on MDI was found. A significant main effect of trait HA on MDI was found, indicating that personality trait HA is a viable vulnerability factor for even sub-clinical depressive symptoms. CONCLUSION This study finds a strong significant relationship between HA and MDI. Moreover, the present study supports the line of research indicating that candidate gene-by-interactions does not increase vulnerability for developing depression even at a sub-clinical level.
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28
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Rashid B, Calhoun V. Towards a brain-based predictome of mental illness. Hum Brain Mapp 2020; 41:3468-3535. [PMID: 32374075 PMCID: PMC7375108 DOI: 10.1002/hbm.25013] [Citation(s) in RCA: 65] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 04/06/2020] [Accepted: 04/06/2020] [Indexed: 01/10/2023] Open
Abstract
Neuroimaging-based approaches have been extensively applied to study mental illness in recent years and have deepened our understanding of both cognitively healthy and disordered brain structure and function. Recent advancements in machine learning techniques have shown promising outcomes for individualized prediction and characterization of patients with psychiatric disorders. Studies have utilized features from a variety of neuroimaging modalities, including structural, functional, and diffusion magnetic resonance imaging data, as well as jointly estimated features from multiple modalities, to assess patients with heterogeneous mental disorders, such as schizophrenia and autism. We use the term "predictome" to describe the use of multivariate brain network features from one or more neuroimaging modalities to predict mental illness. In the predictome, multiple brain network-based features (either from the same modality or multiple modalities) are incorporated into a predictive model to jointly estimate features that are unique to a disorder and predict subjects accordingly. To date, more than 650 studies have been published on subject-level prediction focusing on psychiatric disorders. We have surveyed about 250 studies including schizophrenia, major depression, bipolar disorder, autism spectrum disorder, attention-deficit hyperactivity disorder, obsessive-compulsive disorder, social anxiety disorder, posttraumatic stress disorder, and substance dependence. In this review, we present a comprehensive review of recent neuroimaging-based predictomic approaches, current trends, and common shortcomings and share our vision for future directions.
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Affiliation(s)
- Barnaly Rashid
- Department of PsychiatryHarvard Medical SchoolBostonMassachusettsUSA
| | - Vince Calhoun
- Tri‐Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)Georgia State University, Georgia Institute of Technology, and Emory UniversityAtlantaGeorgiaUSA
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29
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Cropley VL, Tian Y, Fernando K, Mansour L S, Pantelis C, Cocchi L, Zalesky A. Brain-Predicted Age Associates With Psychopathology Dimensions in Youths. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2020; 6:410-419. [PMID: 32981878 DOI: 10.1016/j.bpsc.2020.07.014] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 07/05/2020] [Accepted: 07/20/2020] [Indexed: 11/29/2022]
Abstract
BACKGROUND This study aimed to investigate whether dimensional constructs of psychopathology relate to variation in patterns of brain development and to determine whether these constructs share common neurodevelopmental profiles. METHODS Psychiatric symptom ratings from 9312 youths (8-21 years old) from the Philadelphia Neurodevelopmental Cohort were parsed into 7 independent dimensions of clinical psychopathology representing conduct, anxiety, obsessive-compulsive, attention, depression, bipolar, and psychosis symptoms. Using a subset of this cohort with structural magnetic resonance imaging (n = 1313), a normative model of brain morphology was established and the model was then applied to predict the age of youths with clinical symptoms. We investigated whether the deviation of brain-predicted age from true chronological age, called the brain age gap, explained individual variation in each psychopathology dimension. RESULTS Individual variation in the brain age gap significantly associated with clinical dimensions representing psychosis (t = 3.16, p = .0016), obsessive-compulsive symptoms (t = 2.5, p = .01), and general psychopathology (t = 4.08, p < .0001). Greater symptom severity along these dimensions was associated with brain morphology that appeared older than expected for typically developing youths of the same age. Psychopathology dimensions clustered into 2 modules based on shared brain loci where putative accelerated neurodevelopment was most prominent. Patterns of morphological development were accelerated in frontal cortices for depression, psychosis, and conduct symptoms (module 1), whereas acceleration was most evident in subcortex and insula for the remaining dimensions (module 2). CONCLUSIONS Our findings suggest that increased brain age, particularly in frontal cortex and subcortical nuclei, underpins clinical psychosis and obsessive-compulsive symptoms in youths. Psychopathology dimensions share common neural substrates, despite representing clinically independent symptom profiles.
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Affiliation(s)
- Vanessa L Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia; Centre for Mental Health, Faculty of Health, Arts and Design, School of Health Sciences, Swinburne University, Melbourne, Victoria, Australia.
| | - Ye Tian
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia
| | - Kavisha Fernando
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia
| | - Sina Mansour L
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia; Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia; Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Luca Cocchi
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia; Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
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30
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Hernández-Torrano D, Ibrayeva L, Sparks J, Lim N, Clementi A, Almukhambetova A, Nurtayev Y, Muratkyzy A. Mental Health and Well-Being of University Students: A Bibliometric Mapping of the Literature. Front Psychol 2020; 11:1226. [PMID: 32581976 PMCID: PMC7296142 DOI: 10.3389/fpsyg.2020.01226] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Accepted: 05/11/2020] [Indexed: 01/02/2023] Open
Abstract
The purpose of this study is to map the literature on mental health and well-being of university students using metadata extracted from 5,561 journal articles indexed in the Web of Science database for the period 1975-2020. More specifically, this study uses bibliometric procedures to describe and visually represent the available literature on mental health and well-being in university students in terms of the growth trajectory, productivity, social structure, intellectual structure, and conceptual structure of the field over 45 years. Key findings of the study are that research on mental health and well-being in university students: (a) has experienced a steady growth over the last decades, especially since 2010; (b) is disseminated in a wide range of journals, mainly in the fields of psychology, psychiatry, and education research; (c) is published by scholars with diverse geographical background, although more than half of the publications are produced in the United States; (d) lies on a fragmented research community composed by multiple research groups with little interactions between them; (e) is relatively interdisciplinary and emerges from the convergence of research conducted in the behavioral and biomedical sciences; (f) tends to emphasize pathogenic approaches to mental health (i.e., mental illness); and (g) has mainly addressed seven research topics over the last 45 years: positive mental health, mental disorders, substance abuse, counseling, stigma, stress, and mental health measurement. The findings are discussed, and the implications for the future development of the field are highlighted.
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Affiliation(s)
| | - Laura Ibrayeva
- Graduate School of Education, Nazarbayev University, Nur-Sultan, Kazakhstan
| | - Jason Sparks
- Graduate School of Education, Nazarbayev University, Nur-Sultan, Kazakhstan
| | - Natalya Lim
- Nazarbayev University School of Medicine, Nur-Sultan, Kazakhstan
| | | | | | - Yerden Nurtayev
- Psychological Counseling Center, Nazarbayev University, Nur-Sultan, Kazakhstan
| | - Ainur Muratkyzy
- Graduate School of Education, Nazarbayev University, Nur-Sultan, Kazakhstan
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31
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Rhein C, Mühle C, Lenz B, Richter-Schmidinger T, Kogias G, Boix F, Lourdusamy A, Dörfler A, Peters O, Ramirez A, Jessen F, Maier W, Hüll M, Frölich L, Teipel S, Wiltfang J, Kornhuber J, Müller CP. Association of a CAMK2A genetic variant with logical memory performance and hippocampal volume in the elderly. Brain Res Bull 2020; 161:13-20. [PMID: 32418901 DOI: 10.1016/j.brainresbull.2020.05.001] [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: 02/04/2020] [Revised: 03/31/2020] [Accepted: 05/03/2020] [Indexed: 12/14/2022]
Abstract
Calcium/Calmodulin-dependent kinase alpha (αCaMKII) has been shown to play an essential role in synaptic plasticity and in learning and memory in animal models. However, there is little evidence for an involvement in specific memories in humans. Here we tested the potential involvement of the αCaMKII coding gene CAMK2A in verbal logical memory in two Caucasian populations from Germany, in a sample of 209 elderly people with cognitive impairments and a sample of 142 healthy adults. The association of single nucleotide polymorphisms (SNPs) located within the genomic region of CAMK2A with verbal logical memory learning and retrieval from the Wechsler Memory Scale was measured and hippocampal volume was assessed by structural MRI. In the elderly people, we found the minor allele of CAMK2A intronic SNP rs919741 to predict a higher hippocampal volume and better logical memory retrieval. This association was not found in healthy adults. The present study may provide evidence for an association of a genetic variant of the CAMK2A gene specifically with retrieval of logical memory in elderly humans. This effect is possibly mediated by a higher hippocampal volume.
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Affiliation(s)
- Cosima Rhein
- Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054 Erlangen, Germany
| | - Christiane Mühle
- Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054 Erlangen, Germany
| | - Bernd Lenz
- Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054 Erlangen, Germany; Department of Addictive Behavior and Addiction Medicine, Central Institute of Mental Health (CIMH), Medical Faculty Mannheim, Heidelberg University, Germany
| | - Tanja Richter-Schmidinger
- Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054 Erlangen, Germany
| | - Georgios Kogias
- Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054 Erlangen, Germany
| | - Fernando Boix
- Section for Drug Abuse Research, Department of Forensic Sciences, Oslo University Hospital, Oslo, Norway
| | - Anbarasu Lourdusamy
- Division of Child Health, Obstetrics and Gynecology, School of Medicine, University of Nottingham, NG7 2UH, UK
| | - Arnd Dörfler
- Department of Neuroradiology, University Clinic, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
| | - Oliver Peters
- Department of Psychiatry, Charité-Campus Benjamin Franklin, Eschenallee 3, DE-14050 Berlin, Germany
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, 50937 Cologne, Germany; Department of Neurodegeneration and Geriatric Psychiatry, University of Bonn, 53127 Bonn, Germany
| | - Frank Jessen
- Department of Psychiatry and Psychotherapy, University of Bonn, Sigmund-Freud-Strasse 25, 53105 Bonn, Germany
| | - Wolfgang Maier
- Department of Psychiatry and Psychotherapy, University of Bonn, Sigmund-Freud-Strasse 25, 53105 Bonn, Germany
| | - Michael Hüll
- Emmendingen Center for Psychiatry, Clinic for Geriatric Psychiatry and Psychotherapy and University of Freiburg, Freiburg, Germany
| | - Lutz Frölich
- Central Institute of Mental Health, Mannheim, Germany
| | - Stefan Teipel
- Department of Psychosomatic Medicine, University of Rostock, 18147 Rostock, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen 37075, Germany; German Center for Neurodegenerative Diseases (DZNE), Von-Siebold-Str. 3a, 37075 Goettingen, Germany; Neurosciences and Signalling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054 Erlangen, Germany
| | - Christian P Müller
- Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054 Erlangen, Germany
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32
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Qi S, Bustillo J, Turner JA, Jiang R, Zhi D, Fu Z, Deramus TP, Vergara V, Ma X, Yang X, Stevens M, Zhuo C, Xu Y, Calhoun VD, Sui J. The relevance of transdiagnostic shared networks to the severity of symptoms and cognitive deficits in schizophrenia: a multimodal brain imaging fusion study. Transl Psychiatry 2020; 10:149. [PMID: 32424299 PMCID: PMC7235018 DOI: 10.1038/s41398-020-0834-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 04/06/2020] [Accepted: 04/28/2020] [Indexed: 02/05/2023] Open
Abstract
Schizophrenia (SZ) is frequently concurrent with substance use, depressive symptoms, social communication and attention deficits. However, the relationship between common brain networks (e.g., SZ vs. substance use, SZ vs. depression, SZ vs. developmental disorders) with SZ on specific symptoms and cognition is unclear. Symptom scores were used as a reference to guide fMRI-sMRI fusion for SZ (n = 94), substance use with drinking (n = 313), smoking (n = 104), major depressive disorder (MDD, n = 260), developmental disorders with autism spectrum disorder (ASD, n = 421) and attention-deficit/hyperactivity disorder (ADHD, n = 244) respectively. Common brain regions were determined by overlapping the symptom-related components between SZ and these other groups. Correlation between the identified common brain regions and cognition/symptoms in an independent SZ dataset (n = 144) was also performed. Results show that (1): substance use was related with cognitive deficits in schizophrenia through gray matter volume (GMV) in anterior cingulate cortex and thalamus; (2) depression was linked to PANSS negative dimensions and reasoning in SZ through a network involving caudate-thalamus-middle/inferior temporal gyrus in GMV; (3) developmental disorders pattern was correlated with poor attention, speed of processing and reasoning in SZ through inferior temporal gyrus in GMV. This study reveals symptom driven transdiagnostic shared networks between SZ and other mental disorders via multi-group data mining, indicating that some potential common underlying brain networks associated with schizophrenia differently with respect to symptoms and cognition. These results have heuristic value and advocate specific approaches to refine available treatment strategies for comorbid conditions in schizophrenia.
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Affiliation(s)
- Shile Qi
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA 30303 USA
| | - Juan Bustillo
- grid.266832.b0000 0001 2188 8502Department of Psychiatry, University of New Mexico, Albuquerque, NM 87131 USA
| | - Jessica A. Turner
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA 30303 USA ,grid.256304.60000 0004 1936 7400Department of Psychology, Georgia State University, Atlanta, GA 30302 USA
| | - Rongtao Jiang
- grid.9227.e0000000119573309Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 100190 Beijing, China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences, 100190 Beijing, China
| | - Dongmei Zhi
- grid.9227.e0000000119573309Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 100190 Beijing, China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences, 100190 Beijing, China
| | - Zening Fu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA 30303 USA
| | - Thomas P. Deramus
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA 30303 USA
| | - Victor Vergara
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA 30303 USA
| | - Xiaohong Ma
- grid.412901.f0000 0004 1770 1022Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, 610041 Chengdu, China ,grid.412901.f0000 0004 1770 1022Huaxi Brain Research Center, West China Hospital of Sichuan University, 610041 Chengdu, China
| | - Xiao Yang
- grid.412901.f0000 0004 1770 1022Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, 610041 Chengdu, China ,grid.412901.f0000 0004 1770 1022Huaxi Brain Research Center, West China Hospital of Sichuan University, 610041 Chengdu, China
| | - Mike Stevens
- Olin Neuropsychiatry Research Center, Hartford, CT 06106 USA
| | - Chuanjun Zhuo
- grid.216938.70000 0000 9878 7032Department of Psychiatry, Nankai University Affiliated Anding Hospital, 300222 Tianjin, China
| | - Yong Xu
- grid.263452.40000 0004 1798 4018Department of Humanities and Social Science, Shanxi Medical University, 030001 Taiyuan, China
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA 30303 USA ,grid.256304.60000 0004 1936 7400Department of Psychology, Georgia State University, Atlanta, GA 30302 USA
| | - Jing Sui
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China. .,University of Chinese Academy of Sciences, 100190, Beijing, China. .,Chinese Academy of Sciences Center for Excellence in Brain Science, Institute of Automation, 100190, Beijing, China.
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33
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Frokjaer VG. Pharmacological sex hormone manipulation as a risk model for depression. J Neurosci Res 2020; 98:1283-1292. [PMID: 32399989 PMCID: PMC7383584 DOI: 10.1002/jnr.24632] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 04/06/2020] [Accepted: 04/11/2020] [Indexed: 12/19/2022]
Abstract
Sex hormone transition may trigger severe depressive episodes in some women. In order to map mechanisms related to such phenomena we developed a pharmacological preclinical human model using sex hormone manipulation with gonadotropin releasing hormone agonist (GnRHa) in a placebo‐controlled design. Here the findings from this model is synthesized and discussed in the context of related literature on hormonal contributions to reproductive mental health disorders. The GnRha model work points to an estradiol‐dependent depressive response in healthy women undergoing short‐term sex hormone manipulation with GnRHa, which is linked to serotonin transporter changes (a key regulator of synaptic serotonin), a disengagement of hippocampus, and overengagement of brain networks recruited when processing emotional salient information. Further, the GnRHa model suggest that key brain regions in the reward circuit are less engaged in positive stimuli when undergoing sex hormone manipulation, which may underlie anhedonia. Also, the work supports that enhanced sensitivity to estrogen signaling at the level of gene expression may drive increased risk for depressive symptoms when exposed to sex steroid hormone fluctuations. In conclusion, the GnRHa model work highlights the brain signatures of rapid and profound changes in sex steroid hormone milieu, which reflect plausible mechanisms by which risk for mood disorders works. This model points to the role of estrogen dynamics and sensitivity, and offers a rationale for personalized prevention in hormonal transition phases, for example pregnancy to postpartum transition, perimenopause, and hormone treatments, which now can move into clinical translation and ideally pave the way for protecting mental and cognitive health.
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Affiliation(s)
- Vibe G Frokjaer
- Neurobiology Research Unit and Center for Integrated Molecular Brain Imaging, Copenhagen, Denmark.,Psychiatric Center Copenhagen, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
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34
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Brückl TM, Spoormaker VI, Sämann PG, Brem AK, Henco L, Czamara D, Elbau I, Grandi NC, Jollans L, Kühnel A, Leuchs L, Pöhlchen D, Schneider M, Tontsch A, Keck ME, Schilbach L, Czisch M, Lucae S, Erhardt A, Binder EB. The biological classification of mental disorders (BeCOME) study: a protocol for an observational deep-phenotyping study for the identification of biological subtypes. BMC Psychiatry 2020; 20:213. [PMID: 32393358 PMCID: PMC7216390 DOI: 10.1186/s12888-020-02541-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Accepted: 03/10/2020] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND A major research finding in the field of Biological Psychiatry is that symptom-based categories of mental disorders map poorly onto dysfunctions in brain circuits or neurobiological pathways. Many of the identified (neuro) biological dysfunctions are "transdiagnostic", meaning that they do not reflect diagnostic boundaries but are shared by different ICD/DSM diagnoses. The compromised biological validity of the current classification system for mental disorders impedes rather than supports the development of treatments that not only target symptoms but also the underlying pathophysiological mechanisms. The Biological Classification of Mental Disorders (BeCOME) study aims to identify biology-based classes of mental disorders that improve the translation of novel biomedical findings into tailored clinical applications. METHODS BeCOME intends to include at least 1000 individuals with a broad spectrum of affective, anxiety and stress-related mental disorders as well as 500 individuals unaffected by mental disorders. After a screening visit, all participants undergo in-depth phenotyping procedures and omics assessments on two consecutive days. Several validated paradigms (e.g., fear conditioning, reward anticipation, imaging stress test, social reward learning task) are applied to stimulate a response in a basic system of human functioning (e.g., acute threat response, reward processing, stress response or social reward learning) that plays a key role in the development of affective, anxiety and stress-related mental disorders. The response to this stimulation is then read out across multiple levels. Assessments comprise genetic, molecular, cellular, physiological, neuroimaging, neurocognitive, psychophysiological and psychometric measurements. The multilevel information collected in BeCOME will be used to identify data-driven biologically-informed categories of mental disorders using cluster analytical techniques. DISCUSSION The novelty of BeCOME lies in the dynamic in-depth phenotyping and omics characterization of individuals with mental disorders from the depression and anxiety spectrum of varying severity. We believe that such biology-based subclasses of mental disorders will serve as better treatment targets than purely symptom-based disease entities, and help in tailoring the right treatment to the individual patient suffering from a mental disorder. BeCOME has the potential to contribute to a novel taxonomy of mental disorders that integrates the underlying pathomechanisms into diagnoses. TRIAL REGISTRATION Retrospectively registered on June 12, 2019 on ClinicalTrials.gov (TRN: NCT03984084).
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Affiliation(s)
- Tanja M. Brückl
- grid.419548.50000 0000 9497 5095Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany
| | - Victor I. Spoormaker
- grid.419548.50000 0000 9497 5095Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany
| | - Philipp G. Sämann
- grid.419548.50000 0000 9497 5095Max Planck Institute of Psychiatry, Munich, Germany
| | - Anna-Katharine Brem
- grid.419548.50000 0000 9497 5095Max Planck Institute of Psychiatry, Munich, Germany ,grid.38142.3c000000041936754XBerenson-Allen Center for Noninvasive Brain Stimulation and Division for Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA USA
| | - Lara Henco
- grid.419548.50000 0000 9497 5095Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany
| | - Darina Czamara
- grid.419548.50000 0000 9497 5095Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany
| | - Immanuel Elbau
- grid.419548.50000 0000 9497 5095Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany
| | - Norma C. Grandi
- grid.419548.50000 0000 9497 5095Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany
| | - Lee Jollans
- grid.419548.50000 0000 9497 5095Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany
| | - Anne Kühnel
- grid.419548.50000 0000 9497 5095Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany ,grid.419548.50000 0000 9497 5095International Max Planck Research School – Translational Psychiatry (IMPRS-TP), Max Planck Institute of Psychiatry, Munich, Germany
| | - Laura Leuchs
- grid.419548.50000 0000 9497 5095Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany
| | - Dorothee Pöhlchen
- grid.419548.50000 0000 9497 5095Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany ,grid.419548.50000 0000 9497 5095International Max Planck Research School – Translational Psychiatry (IMPRS-TP), Max Planck Institute of Psychiatry, Munich, Germany
| | - Maximilian Schneider
- grid.419548.50000 0000 9497 5095Max Planck Institute of Psychiatry, Munich, Germany
| | - Alina Tontsch
- grid.419548.50000 0000 9497 5095Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany
| | - Martin E. Keck
- grid.419548.50000 0000 9497 5095Max Planck Institute of Psychiatry, Munich, Germany
| | - Leonhard Schilbach
- grid.419548.50000 0000 9497 5095Independent Max Planck Research Group for Social Neuroscience, Max Planck Institute of Psychiatry, Munich, Germany
| | - Michael Czisch
- grid.419548.50000 0000 9497 5095Max Planck Institute of Psychiatry, Munich, Germany
| | - Susanne Lucae
- grid.419548.50000 0000 9497 5095Max Planck Institute of Psychiatry, Munich, Germany
| | - Angelika Erhardt
- grid.419548.50000 0000 9497 5095Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany
| | - Elisabeth B. Binder
- grid.419548.50000 0000 9497 5095Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804 Munich, Germany ,grid.189967.80000 0001 0941 6502Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, USA
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Li J, Yang X, Zhou F, Liu C, Wei Z, Xin F, Daumann B, Daumann J, Kendrick KM, Becker B. Modafinil enhances cognitive, but not emotional conflict processing via enhanced inferior frontal gyrus activation and its communication with the dorsomedial prefrontal cortex. Neuropsychopharmacology 2020; 45:1026-1033. [PMID: 31995813 PMCID: PMC7162953 DOI: 10.1038/s41386-020-0625-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Revised: 01/07/2020] [Accepted: 01/15/2020] [Indexed: 02/05/2023]
Abstract
Cognitive control regulates cognitive and emotional systems to facilitate goal-directed behavior in the context of task-irrelevant distractors. Cognitive control deficits contribute to residual functional impairments across psychiatric disorders and represent a promising novel treatment target. Translational evidence suggests that modafinil may enhance performance in executive functions; however, differential effects on regulatory control in cognitive and emotional domains have not been examined. The present pre-registered randomized-controlled pharmacological fMRI trial examined differential effects of modafinil (single-dose, 200 mg) on cognitive and emotional conflict processing. To further separate objective cognitive enhancing effects from subjective performance perception, a metacognitive paradigm was employed. Results indicated that modafinil specifically enhanced cognitive conflict performance and concomitantly increased activation in the inferior frontal gyrus and its functional communication with the dorsomedial prefrontal cortex. Exploratory analysis further revealed modafinil-enhanced basolateral amygdala reactivity to cognitive conflict, with stronger reactivity being associated with higher cognitive conflict performance. Whereas modafinil enhanced cognitive performance in the metacognitive paradigm, confidence indices remained unaffected. Overall, the present results suggest that modafinil has the potential to enhance cognitive conflict processing while leaving emotional conflict processing unaffected. On the neural level modafinil enhanced the recruitment of a network engaged in general conflict and regulatory control processes, whereas effects on the amygdala may reflect improved arousal-mediated attention processes for conflicting information. The pattern of cognitive enhancing effects in the absence of effects on affective processing suggests a promising potential to enhance cognitive control in clinical populations.
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Affiliation(s)
- Jialin Li
- 0000 0004 0369 4060grid.54549.39The Clinical Hospital of the Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Xi Yang
- 0000 0004 0369 4060grid.54549.39The Clinical Hospital of the Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Feng Zhou
- 0000 0004 0369 4060grid.54549.39The Clinical Hospital of the Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Congcong Liu
- 0000 0004 0369 4060grid.54549.39The Clinical Hospital of the Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Zhenyu Wei
- 0000 0004 0369 4060grid.54549.39The Clinical Hospital of the Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Fei Xin
- 0000 0004 0369 4060grid.54549.39The Clinical Hospital of the Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | | | - Jörg Daumann
- 0000 0000 8580 3777grid.6190.eDepartment of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany
| | - Keith M. Kendrick
- 0000 0004 0369 4060grid.54549.39The Clinical Hospital of the Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Benjamin Becker
- The Clinical Hospital of the Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.
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Balanzá-Martínez V, Shansis FM, Tatay-Manteiga A, López-García P. Diet and Neurocognition in Mood Disorders - An Overview of the Overlooked. Curr Pharm Des 2020; 26:2353-2362. [PMID: 32188376 DOI: 10.2174/1381612826666200318152530] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Accepted: 02/27/2020] [Indexed: 01/02/2023]
Abstract
Bipolar disorder and major depression are associated with significant disability, morbidity, and reduced life expectancy. People with mood disorders have shown higher ratios of unhealthy lifestyle choices, including poor diet quality and suboptimal nutrition. Diet and nutrition impact on brain /mental health, but cognitive outcomes have been less researched in psychiatric disorders. Neurocognitive dysfunction is a major driver of social dysfunction and a therapeutic target in mood disorders, although effective cognitive-enhancers are currently lacking. This narrative review aimed to assess the potential cognitive benefits of dietary and nutritional interventions in subjects diagnosed with mood disorders. Eight clinical trials with nutrients were identified, whereas none involved dietary interventions. Efficacy to improve select cognitive deficits has been reported, but results are either preliminary or inconsistent. Methodological recommendations for future cognition trials in the field are advanced. Current evidence and future views are discussed from the perspectives of precision medicine, clinical staging, nutritional psychiatry, and the brain-gut-microbiota axis.
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Affiliation(s)
- Vicent Balanzá-Martínez
- Teaching Unit of Psychiatry, Department of Medicine, University of Valencia, Valencia, Spain.,Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Flavio M Shansis
- Centro de Pesquisa Translacional en Transtorno del Humor y Suicidio (CEPETTHS), Programa de Pos Grado en Ciencias Medicas, Universidade do Vale do Taquari (Univates), Lajeado, Brazil
| | | | - Pilar López-García
- Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.,Department of Psychiatry. Faculty of Medicine, Universidad Autonoma de Madrid, Madrid, Spain.,Instituto de Investigación Sanitaria Princesa (IIS Princesa), Madrid, Spain
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37
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Burke Quinlan E, Banaschewski T, Barker GJ, Bokde AL, Bromberg U, Büchel C, Desrivières S, Flor H, Frouin V, Garavan H, Heinz A, Brühl R, Martinot JL, Paillère Martinot ML, Nees F, Papadopoulos Orfanos D, Paus T, Poustka L, Hohmann S, Smolka MN, Fröhner JH, Walter H, Whelan R, Schumann G. Identifying biological markers for improved precision medicine in psychiatry. Mol Psychiatry 2020; 25:243-253. [PMID: 31676814 PMCID: PMC6978138 DOI: 10.1038/s41380-019-0555-5] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 07/16/2019] [Accepted: 08/19/2019] [Indexed: 01/24/2023]
Abstract
Mental disorders represent an increasing personal and financial burden and yet treatment development has stagnated in recent decades. Current disease classifications do not reflect psychobiological mechanisms of psychopathology, nor the complex interplay of genetic and environmental factors, likely contributing to this stagnation. Ten years ago, the longitudinal IMAGEN study was designed to comprehensively incorporate neuroimaging, genetics, and environmental factors to investigate the neural basis of reinforcement-related behavior in normal adolescent development and psychopathology. In this article, we describe how insights into the psychobiological mechanisms of clinically relevant symptoms obtained by innovative integrative methodologies applied in IMAGEN have informed our current and future research aims. These aims include the identification of symptom groups that are based on shared psychobiological mechanisms and the development of markers that predict disease course and treatment response in clinical groups. These improvements in precision medicine will be achieved, in part, by employing novel methodological tools that refine the biological systems we target. We will also implement our approach in low- and medium-income countries to understand how distinct environmental, socioeconomic, and cultural conditions influence the development of psychopathology. Together, IMAGEN and related initiatives strive to reduce the burden of mental disorders by developing precision medicine approaches globally.
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Affiliation(s)
- Erin Burke Quinlan
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King’s College London, United Kingdom
| | - 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
| | - Gareth J. Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
| | - Arun L.W. Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Uli Bromberg
- University Medical Centre Hamburg-Eppendorf, House W34, 3.OG, Martinistr. 52, 20246, Hamburg, Germany
| | - Christian Büchel
- University Medical Centre Hamburg-Eppendorf, House W34, 3.OG, Martinistr. 52, 20246, Hamburg, Germany
| | - 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
| | - Vincent Frouin
- NeuroSpin, CEA, Université Paris-Saclay, F-91191 Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, 05405 Burlington, Vermont, USA
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Charitéplatz 1, Berlin, Germany
| | - Rüdiger Brühl
- 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 Unit 1000 “Neuroimaging & Psychiatry”, University Paris Sud – Paris Saclay, University Paris Descartes; DIGITEO labs, Gif sur Yvette; France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 “Neuroimaging & Psychiatry”, University Paris Sud – Paris Saclay, University Paris Descartes; and AP-HP.Sorbonne Université, Department of Adolescent Psychopathology and Medicine, Maison de Solenn, Cochin 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,University Medical Centre Hamburg-Eppendorf, House W34, 3.OG, Martinistr. 52, 20246, Hamburg, Germany
| | | | - Tomáš Paus
- Rotman Research Institute, Baycrest and Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, M6A 2E1, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Michael N. Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Juliane H. Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Charitéplatz 1, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Ireland
| | - Gunter Schumann
- PONS Research Group, Dept of Psychiatry and Psychotherapy, Campus Charite Mitte, Humboldt University, Berlin and Leibniz Institute for Neurobiology, Magdeburg, Germany, and Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, P.R. China
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38
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Animal models of liability to post-traumatic stress disorder: going beyond fear memory. Behav Pharmacol 2020; 30:122-129. [PMID: 30724805 DOI: 10.1097/fbp.0000000000000475] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
In this review, we advocate a dimensional approach on the basis of candidate endophenotypes to the development of animal models of post-traumatic stress disorder (PTSD) capable of including genetic liability factors, variations in symptoms profile and underlying neurobiological mechanisms, and specific comorbidities. Results from the clinical literature pointed to two candidate endophenotypes of PTSD: low sensory gating and high waiting impulsivity. Findings of comparative studies in mice of two inbred strains characterized by different expressions of the two candidate endophenotypes showed different strain-specific neural and behavioral effects of stress experiences. Thus, mice of the standard C57BL/6J strain show stress-induced helplessness, stress-learned helplessness, and stress-extinction-resistant conditioned freezing. Instead, mice of the genetically unrelated DBA/2J strain, expressing both candidate endophenotypes, show stress-induced extinction-resistant avoidance and neural and behavioral phenotypes promoted by prolonged exposure to addictive drugs. These strain differences are in line with evidence of associations between genetic variants and specific stress-promoted pathological profiles in PTSD, support a role of genotype in determining different PTSD comorbidities, and offer the means to investigate specific pathogenic processes.
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39
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Müller CP. Lasting translation: how to improve animal models for addiction treatment. Addiction 2020; 115:13-14. [PMID: 31576616 DOI: 10.1111/add.14788] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 08/05/2019] [Indexed: 12/27/2022]
Affiliation(s)
- Christian P Müller
- Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander-University of Erlangen-Nuremberg, Erlangen, Germany
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40
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41
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Wolfers T, Beckmann CF, Hoogman M, Buitelaar JK, Franke B, Marquand AF. Individual differences v. the average patient: mapping the heterogeneity in ADHD using normative models. Psychol Med 2020; 50:314-323. [PMID: 30782224 PMCID: PMC7083555 DOI: 10.1017/s0033291719000084] [Citation(s) in RCA: 77] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2018] [Revised: 01/04/2019] [Accepted: 01/08/2019] [Indexed: 12/26/2022]
Abstract
BACKGROUND The present paper presents a fundamentally novel approach to model individual differences of persons with the same biologically heterogeneous mental disorder. Unlike prevalent case-control analyses, that assume a clear distinction between patient and control groups and thereby introducing the concept of an 'average patient', we describe each patient's biology individually, gaining insights into the different facets that characterize persistent attention-deficit/hyperactivity disorder (ADHD). METHODS Using a normative modeling approach, we mapped inter-individual differences in reference to normative structural brain changes across the lifespan to examine the degree to which case-control analyses disguise differences between individuals. RESULTS At the level of the individual, deviations from the normative model were frequent in persistent ADHD. However, the overlap of more than 2% between participants with ADHD was only observed in few brain loci. On average, participants with ADHD showed significantly reduced gray matter in the cerebellum and hippocampus compared to healthy individuals. While the case-control differences were in line with the literature on ADHD, individuals with ADHD only marginally reflected these group differences. CONCLUSIONS Case-control comparisons, disguise inter-individual differences in brain biology in individuals with persistent ADHD. The present results show that the 'average ADHD patient' has limited informative value, providing the first evidence for the necessity to explore different biological facets of ADHD at the level of the individual and practical means to achieve this end.
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Affiliation(s)
- Thomas Wolfers
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Christian F. Beckmann
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
- Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, UK
| | - Martine Hoogman
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Jan K. Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
- Karakter Child and Adolescent Psychiatry University Center, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Barbara Franke
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Psychiatry, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Andre F. Marquand
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Neuroimaging, Institute of Psychiatry, King's College London, London, UK
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42
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Durstewitz D, Koppe G, Meyer-Lindenberg A. Deep neural networks in psychiatry. Mol Psychiatry 2019; 24:1583-1598. [PMID: 30770893 DOI: 10.1038/s41380-019-0365-9] [Citation(s) in RCA: 101] [Impact Index Per Article: 20.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Revised: 01/02/2019] [Accepted: 01/24/2019] [Indexed: 01/03/2023]
Abstract
Machine and deep learning methods, today's core of artificial intelligence, have been applied with increasing success and impact in many commercial and research settings. They are powerful tools for large scale data analysis, prediction and classification, especially in very data-rich environments ("big data"), and have started to find their way into medical applications. Here we will first give an overview of machine learning methods, with a focus on deep and recurrent neural networks, their relation to statistics, and the core principles behind them. We will then discuss and review directions along which (deep) neural networks can be, or already have been, applied in the context of psychiatry, and will try to delineate their future potential in this area. We will also comment on an emerging area that so far has been much less well explored: by embedding semantically interpretable computational models of brain dynamics or behavior into a statistical machine learning context, insights into dysfunction beyond mere prediction and classification may be gained. Especially this marriage of computational models with statistical inference may offer insights into neural and behavioral mechanisms that could open completely novel avenues for psychiatric treatment.
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Affiliation(s)
- Daniel Durstewitz
- Department of Theoretical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, 68159, Mannheim, Germany.
| | - Georgia Koppe
- Department of Theoretical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, 68159, Mannheim, Germany.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, 68159, Mannheim, Germany
| | - Andreas Meyer-Lindenberg
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim/Heidelberg University, 68159, Mannheim, Germany
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Scott J, Hidalgo-Mazzei D, Strawbridge R, Young A, Resche-Rigon M, Etain B, Andreassen OA, Bauer M, Bennabi D, Blamire AM, Boumezbeur F, Brambilla P, Cattane N, Cattaneo A, Chupin M, Coello K, Cointepas Y, Colom F, Cousins DA, Dubertret C, Duchesnay E, Ferro A, Garcia-Estela A, Goikolea J, Grigis A, Haffen E, Høegh MC, Jakobsen P, Kalman JL, Kessing LV, Klohn-Saghatolislam F, Lagerberg TV, Landén M, Lewitzka U, Lutticke A, Mazer N, Mazzelli M, Mora C, Muller T, Mur-Mila E, Oedegaard KJ, Oltedal L, Pålsson E, Papadopoulos Orfanos D, Papiol S, Perez-Sola V, Reif A, Ritter P, Rossi R, Schulze T, Senner F, Smith FE, Squarcina L, Steen NE, Thelwall PE, Varo C, Vieta E, Vinberg M, Wessa M, Westlye LT, Bellivier F. Prospective cohort study of early biosignatures of response to lithium in bipolar-I-disorders: overview of the H2020-funded R-LiNK initiative. Int J Bipolar Disord 2019; 7:20. [PMID: 31552554 PMCID: PMC6760458 DOI: 10.1186/s40345-019-0156-x] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Accepted: 07/24/2019] [Indexed: 01/01/2023] Open
Abstract
Background Lithium is recommended as a first line treatment for bipolar disorders. However, only 30% of patients show an optimal outcome and variability in lithium response and tolerability is poorly understood. It remains difficult for clinicians to reliably predict which patients will benefit without recourse to a lengthy treatment trial. Greater precision in the early identification of individuals who are likely to respond to lithium is a significant unmet clinical need. Structure The H2020-funded Response to Lithium Network (R-LiNK; http://www.r-link.eu.com/) will undertake a prospective cohort study of over 300 individuals with bipolar-I-disorder who have agreed to commence a trial of lithium treatment following a recommendation by their treating clinician. The study aims to examine the early prediction of lithium response, non-response and tolerability by combining systematic clinical syndrome subtyping with examination of multi-modal biomarkers (or biosignatures), including omics, neuroimaging, and actigraphy, etc. Individuals will be followed up for 24 months and an independent panel will assess and classify each participants’ response to lithium according to predefined criteria that consider evidence of relapse, recurrence, remission, changes in illness activity or treatment failure (e.g. stopping lithium; new prescriptions of other mood stabilizers) and exposure to lithium. Novel elements of this study include the recruitment of a large, multinational, clinically representative sample specifically for the purpose of studying candidate biomarkers and biosignatures; the application of lithium-7 magnetic resonance imaging to explore the distribution of lithium in the brain; development of a digital phenotype (using actigraphy and ecological momentary assessment) to monitor daily variability in symptoms; and economic modelling of the cost-effectiveness of introducing biomarker tests for the customisation of lithium treatment into clinical practice. Also, study participants with sub-optimal medication adherence will be offered brief interventions (which can be delivered via a clinician or smartphone app) to enhance treatment engagement and to minimize confounding of lithium non-response with non-adherence. Conclusions The paper outlines the rationale, design and methodology of the first study being undertaken by the newly established R-LiNK collaboration and describes how the project may help to refine the clinical response phenotype and could translate into the personalization of lithium treatment. Electronic supplementary material The online version of this article (10.1186/s40345-019-0156-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jan Scott
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK.,Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Université Paris Diderot, 75013, Paris, France
| | - Diego Hidalgo-Mazzei
- Bipolar and Depressive Disorders Unit, Department of Psychiatry and Psychology, Institute of Neurosciences, Hospital Clinic de Barcelona, University of Barcelona, IDIBAPS, CIBERSAM, Villaroel 170, 08036, Barcelona, Catalonia, Spain
| | - Rebecca Strawbridge
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Allan Young
- Centre for Affective Disorders, Department of Psychological Medicine, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Matthieu Resche-Rigon
- Université Paris Diderot, 75013, Paris, France.,Service de Biostatistique et Information Médicale, Hôpital Saint-Louis, AP-HP, Paris, France.,Inserm, UMR 1153, Equipe ECSTRA, Paris, France
| | - Bruno Etain
- Université Paris Diderot, 75013, Paris, France.,Département de Psychiatrie et de Médecine Addictologique, AP-HP, GH Saint-Louis - Lariboisière - F. Widal, 75475, Paris, France.,Inserm, U1144, Team 1, 75006, Paris, France
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Michael Bauer
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Djamila Bennabi
- Department of Clinical Psychiatry, Inserm CIC 1431, CHU Besançon, 25000, Besançon, France.,Laboratoire de Neurosciences, Université Bourgogne Franche-Comté, 25000, Besançon, France
| | - Andrew M Blamire
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK.,Newcastle Magnetic Resonance Centre, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Fawzi Boumezbeur
- NeuroSpin, CEA, Université Paris-Saclay, 91191, Gif-sur-Yvette, France
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy.,Department of Psychiatry and Behavioural Neurosciences, University of Texas at Houston, Houston, TX, USA
| | - Nadia Cattane
- IRCCS Istituto Centro San Giovanni di Dio - Fatebenefratelli, Brescia, Italy
| | - Annamaria Cattaneo
- IRCCS Istituto Centro San Giovanni di Dio - Fatebenefratelli, Brescia, Italy
| | - Marie Chupin
- CATI Neuroimaging Platform, ICM, Pitié Salpétrière Hospital, 75013, Paris, France.,Institut du Cerveau et de la Moelle épinière, ICM, 75013, Paris, France.,Inserm, U1127, 75013, Paris, France.,CNRS, UMR 7225, 75013, Paris, France.,Sorbonne Université, 75013, Paris, France
| | - Klara Coello
- Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, University Hospital of Copenhagen, Copenhagen, Denmark
| | - Yann Cointepas
- NeuroSpin, CEA, Université Paris-Saclay, 91191, Gif-sur-Yvette, France.,CATI Neuroimaging Platform, ICM, Pitié Salpétrière Hospital, 75013, Paris, France
| | - Francesc Colom
- Mental Health Research Program, IMIM, Hospital del Mar, CIBERSAM, Barcelona, Catalonia, Spain
| | - David A Cousins
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK.,Northumberland Tyne and Wear NHS Foundation Trust, Newcastle upon Tyne, NE3 3XT, UK
| | - Caroline Dubertret
- Université Paris Diderot, 75013, Paris, France.,APHP; Psychiatry Department, University Hospital Louis Mourier, Colombes, France.,INSERM U894, Institute of Psychiatry and Neurosciences of Paris, Paris, France
| | - Edouard Duchesnay
- NeuroSpin, CEA, Université Paris-Saclay, 91191, Gif-sur-Yvette, France
| | - Adele Ferro
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
| | - Aitana Garcia-Estela
- Mental Health Research Program, IMIM, Hospital del Mar, CIBERSAM, Barcelona, Catalonia, Spain
| | - Jose Goikolea
- Bipolar and Depressive Disorders Unit, Department of Psychiatry and Psychology, Institute of Neurosciences, Hospital Clinic de Barcelona, University of Barcelona, IDIBAPS, CIBERSAM, Villaroel 170, 08036, Barcelona, Catalonia, Spain
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, 91191, Gif-sur-Yvette, France
| | - Emmanuel Haffen
- Department of Clinical Psychiatry, Inserm CIC 1431, CHU Besançon, 25000, Besançon, France.,Laboratoire de Neurosciences, Université Bourgogne Franche-Comté, 25000, Besançon, France
| | - Margrethe C Høegh
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Petter Jakobsen
- NORMENT, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway.,Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Janos L Kalman
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany.,Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany.,International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
| | - Lars V Kessing
- Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, University Hospital of Copenhagen, Copenhagen, Denmark
| | - Farah Klohn-Saghatolislam
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany.,Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Trine V Lagerberg
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Mikael Landén
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Ute Lewitzka
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Ashley Lutticke
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany.,Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Nicolas Mazer
- APHP; Psychiatry Department, University Hospital Louis Mourier, Colombes, France.,INSERM U894, Institute of Psychiatry and Neurosciences of Paris, Paris, France
| | - Monica Mazzelli
- IRCCS Istituto Centro San Giovanni di Dio - Fatebenefratelli, Brescia, Italy
| | - Cristina Mora
- IRCCS Istituto Centro San Giovanni di Dio - Fatebenefratelli, Brescia, Italy
| | - Thorsten Muller
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Estanislao Mur-Mila
- Mental Health Research Program, IMIM, Hospital del Mar, CIBERSAM, Barcelona, Catalonia, Spain
| | - Ketil Joachim Oedegaard
- NORMENT, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway.,Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Leif Oltedal
- Department of Clinical Medicine, University of Bergen, Bergen, Norway.,Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Erik Pålsson
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | | | - Sergi Papiol
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany.,Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Victor Perez-Sola
- Mental Health Research Program, IMIM, Hospital del Mar, CIBERSAM, Barcelona, Catalonia, Spain
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Philipp Ritter
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Roberto Rossi
- Unit of Psychiatry, IRCCS Istituto Centro San Giovanni di Dio - Fatebenefratelli, Brescia, Italy
| | - Thomas Schulze
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany
| | - Fanny Senner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Munich, Germany.,Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Fiona E Smith
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK.,Newcastle Magnetic Resonance Centre, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Letizia Squarcina
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
| | - Nils Eiel Steen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Pete E Thelwall
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, NE1 7RU, UK.,Newcastle Magnetic Resonance Centre, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Cristina Varo
- Bipolar and Depressive Disorders Unit, Department of Psychiatry and Psychology, Institute of Neurosciences, Hospital Clinic de Barcelona, University of Barcelona, IDIBAPS, CIBERSAM, Villaroel 170, 08036, Barcelona, Catalonia, Spain
| | - Eduard Vieta
- Bipolar and Depressive Disorders Unit, Department of Psychiatry and Psychology, Institute of Neurosciences, Hospital Clinic de Barcelona, University of Barcelona, IDIBAPS, CIBERSAM, Villaroel 170, 08036, Barcelona, Catalonia, Spain
| | - Maj Vinberg
- Copenhagen Affective Disorder Research Center (CADIC), Psychiatric Center Copenhagen, University Hospital of Copenhagen, Copenhagen, Denmark
| | - Michele Wessa
- Department of Clinical Psychology and Neuropsychology, Institute for Psychology, Johannes Gutenberg-University Mainz, Wallstraße 3, 55122, Mainz, Germany
| | - Lars T Westlye
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.,Department of Psychology, University of Oslo, Oslo, Norway
| | - Frank Bellivier
- Université Paris Diderot, 75013, Paris, France. .,Département de Psychiatrie et de Médecine Addictologique, AP-HP, GH Saint-Louis - Lariboisière - F. Widal, 75475, Paris, France. .,Inserm, U1144, Team 1, 75006, Paris, France.
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Brietzke E, Hawken ER, Idzikowski M, Pong J, Kennedy SH, Soares CN. Integrating digital phenotyping in clinical characterization of individuals with mood disorders. Neurosci Biobehav Rev 2019; 104:223-230. [DOI: 10.1016/j.neubiorev.2019.07.009] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 07/08/2019] [Accepted: 07/15/2019] [Indexed: 12/26/2022]
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Personalized and precision medicine as informants for treatment management of bipolar disorder. Int Clin Psychopharmacol 2019; 34:189-205. [PMID: 30932919 DOI: 10.1097/yic.0000000000000260] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
DSM-5 diagnostic categories, defined by a set of psychopathological symptoms are heterogeneous conditions that may include different biological entities, with distinct etiopathogenesis, different courses and requiring different treatment management. For bipolar disorder the major evidences for this lack of validity are the long paths before a proper diagnosis, the inconsistence of treatment guidelines, the long phases of pharmacological adjustment and the low average of long-term treatment response rates. Personalized medicine for mental disorders aims to couple established clinical-pathological indexes with new molecular profiling to create diagnostic, prognostic and therapeutic strategies precisely tailored to each patient. Regarding bipolar disorder, the clinical history and presentation are still the most reliable markers in stratifying patients and guiding therapeutic management, despite the research goes to great lengths to develop new neuropsychological or biological markers that can reliably predict individual therapy effectiveness. We provide an overview of the advancements in personalized medicine in bipolar disorder, with particular attention to how psychopathology, age at onset, comorbidity, course and staging, genetic and epigenetic, imaging and biomarkers can influence treatment management and provide an integration to the conventional treatment guidelines. This approach may offer a new and rational path for the development of treatments for targeted subgroups of patients with bipolar disorder.
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Abstract
The biological mechanisms underlying psychiatric diagnoses are not well defined. Clinical diagnosis based on categorical systems exhibit high levels of heterogeneity and co-morbidity. The Research Domain Criteria (RDoC) attempts to reconceptualize psychiatric disorders into transdiagnostic functional dimensional constructs based on neurobiological measures and observable behaviour. By understanding the underlying neurobiology and pathophysiology of the relevant processes, the RDoC aims to advance biomarker development for disease prediction and treatment response. This important evolving dimensional framework must also consider environmental factors. Emerging evidence suggests that gut microbes (microbiome) play a physiological role in brain diseases by modulating neuroimmune, neuroendocrine and neural signalling pathways between the gut and the brain. The integration of the gut microbiome signature as an additional dimensional component of the RDoC may enhance precision psychiatry.
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47
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Müller CP, Chu C, Qin L, Liu C, Xu B, Gao H, Ruggeri B, Hieber S, Schneider J, Jia T, Tay N, Akira S, Satoh T, Banaschewski T, Bokde ALW, Bromberg U, Büchel C, Quinlan EB, Flor H, Frouin V, Garavan H, Gowland P, Heinz A, Ittermann B, Martinot JL, Martinot MLP, Artiges E, Lemaitre H, Nees F, Papadopoulos Orfanos D, Paus T, Poustka L, Millenet S, Fröhner JH, Smolka MN, Walter H, Whelan R, Bakalkin G, Liu Y, Desrivières S, Elliott P, Eulenburg V, Levy D, Crews F, Schumann G. The Cortical Neuroimmune Regulator TANK Affects Emotional Processing and Enhances Alcohol Drinking: A Translational Study. Cereb Cortex 2019; 29:1736-1751. [PMID: 30721969 PMCID: PMC6430980 DOI: 10.1093/cercor/bhy341] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Revised: 12/14/2018] [Accepted: 12/19/2018] [Indexed: 12/22/2022] Open
Abstract
Alcohol abuse is a major public health problem worldwide. Understanding the molecular mechanisms that control regular drinking may help to reduce hazards of alcohol consumption. While immunological mechanisms have been related to alcohol drinking, most studies reported changes in immune function that are secondary to alcohol use. In this report, we analyse how the gene "TRAF family member-associated NF-κB activator" (TANK) affects alcohol drinking behavior. Based on our recent discovery in a large GWAS dataset that suggested an association of TANK, SNP rs197273, with alcohol drinking, we report that SNP rs197273 in TANK is associated both with gene expression (P = 1.16 × 10-19) and regional methylation (P = 5.90 × 10-25). A tank knock out mouse model suggests a role of TANK in alcohol drinking, anxiety-related behavior, as well as alcohol exposure induced activation of insular cortex NF-κB. Functional and structural neuroimaging studies among up to 1896 adolescents reveal that TANK is involved in the control of brain activity in areas of aversive interoceptive processing, including the insular cortex, but not in areas related to reinforcement, reward processing or impulsiveness. Our findings suggest that the cortical neuroimmune regulator TANK is associated with enhanced aversive emotional processing that better protects from the establishment of alcohol drinking behavior.
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Affiliation(s)
- Christian P Müller
- Section of Addiction Medicine, Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, Erlangen, Germany
| | - Congying Chu
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College De Crespigny Park, London, UK
| | - Liya Qin
- Bowles Center for Alcohol Studies, School of Medicine, University of North Carolina, Chapel Hill NC, USA
| | - Chunyu Liu
- The Framingham Heart Study, 73 Mt Wayte Ave, Framingham MA, USA
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda MD, USA
- Boston University School of Public Health, 715 Albany St, Boston MA, USA
| | - Bing Xu
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College De Crespigny Park, London, UK
| | - He Gao
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Barbara Ruggeri
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College De Crespigny Park, London, UK
| | - Saskia Hieber
- Section of Addiction Medicine, Department of Psychiatry and Psychotherapy, University Clinic, Friedrich-Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, Erlangen, Germany
| | - Julia Schneider
- Institute for Biochemistry and Molecular Medicine, Friedrich-Alexander-University Erlangen-Nuremberg, Fahrstrasse 17, Erlangen, Germany
| | - Tianye Jia
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College De Crespigny Park, London, UK
| | - Nicole Tay
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College De Crespigny Park, London, UK
| | - Shizuo Akira
- Laboratory of Host Defense, World Premier International Immunology Frontiern Research Center, Research Institute for Microbial Diseases, Osaka University, 1-1 Yamadaoka, Suita, Osaka, Osaka, Japan
| | - Takashi Satoh
- Laboratory of Host Defense, World Premier International Immunology Frontiern Research Center, Research Institute for Microbial Diseases, Osaka University, 1-1 Yamadaoka, Suita, Osaka, Osaka, Japan
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, James's Street, Dublin, Ireland
| | - Uli Bromberg
- University Medical Centre Hamburg-Eppendorf, House W34, 3.OG, Martinistr. 52, Hamburg, Germany
| | - Christian Büchel
- University Medical Centre Hamburg-Eppendorf, House W34, 3.OG, Martinistr. 52, Hamburg, Germany
| | - Erin Burke Quinlan
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College De Crespigny Park, London, UK
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Vincent Frouin
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Charitéplatz 1, Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany [ Physikalisch-Technische Bundesanstalt (PTB), Abbestr. 2—12, Berlin, Germany]
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 “Neuroimaging & Psychiatry”, University Paris Sud—University Paris Saclay, DIGITEO Labs, Rue Noetzlin, Gif sur Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 “Neuroimaging & Psychiatry”, University Paris Sud—Paris Saclay, University Paris Descartes; and AP-HP, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, 47-83, boulevard de l'Hôpital, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 “Neuroimaging & Psychiatry”, University Paris Sud—University Paris Saclay, DIGITEO Labs, Gif sur Yvette; and Psychiatry Department, Orsay Hospital, Orsay, France
| | - Herve Lemaitre
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 “Neuroimaging & Psychiatry”, University Paris-Sud Medical School, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, Mannheim, Germany
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, Mannheim, Germany
| | | | - Tomáš Paus
- Rotman Research Institute, Baycrest and Departments of Psychology and Psychiatry, University of Toronto, 3560 Bathurst Street, Toronto, Ontario, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, Göttingen, Germany
- Clinic for Child and Adolescent Psychiatry, Medical University of Vienna, Währinger Gürtel 18-20, Vienna, Austria
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Chemnitzer Str. 46a01187 Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Chemnitzer Str. 46a01187 Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Charitéplatz 1, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Aras an Phiarsaigh Trinity College Dublin, Dublin, Ireland
| | - Georgy Bakalkin
- Division of Biological Research on Drug Dependence, Department of Pharmaceutical, Biosciences, Uppsala University, Husargatan 3, Uppsala, Sweden
| | - Yun Liu
- Key Laboratory of Metabolism and Molecular Medicine, Ministry of Education; Department of Biochemistry and Molecular Biology, Fudan University Shanghai Medical College, Shanghai, P.R. China
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College De Crespigny Park, London, UK
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Volker Eulenburg
- Institute for Biochemistry and Molecular Medicine, Friedrich-Alexander-University Erlangen-Nuremberg, Fahrstrasse 17, Erlangen, Germany
- Department of Anaesthesiology and Intensive Care Medicine, University of Leipzig, Liebigstrasse 20, Leipzig, Germany
| | - Daniel Levy
- The Framingham Heart Study, 73 Mt Wayte Ave, Framingham MA, USA
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda MD, USA
| | - Fulton Crews
- Bowles Center for Alcohol Studies, School of Medicine, University of North Carolina, Chapel Hill NC, USA
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College De Crespigny Park, London, UK
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Symptoms are not the solution but the problem: Why psychiatric research should focus on processes rather than symptoms. Behav Brain Sci 2019; 42:e7. [DOI: 10.1017/s0140525x18001000] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
AbstractProgress in psychiatric research has been hindered by the use of artificial disease categories to map distinct biological substrates. Efforts to overcome this obstacle have led to the misconception that relevant psychiatric dimensions are not biologically reducible. Consequently, the return to phenomenology is once again advocated. We propose a process-centered paradigm of biological reduction compatible with non-reductive materialism.
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Abstract
AbstractBorsboom and colleagues argue that reductionism in psychopathology research has not provided the expected insights. Instead, they suggest a systems approach of interacting syndromes, which, however, falls short of a perspective for empirical testing. Here, a combination of both approaches is suggested: a reductionistic empirical approach allowing testability, synergistic with a constructivistic systems appraisal of syndrome networks – a constructive reductionism.
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Wang AL, Chao OY, Yang YM, Trossbach SV, Müller CP, Korth C, Huston JP, de Souza Silva MA. Anxiogenic-like behavior and deficient attention/working memory in rats expressing the human DISC1 gene. Pharmacol Biochem Behav 2019; 179:73-79. [PMID: 30779934 DOI: 10.1016/j.pbb.2019.02.005] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 02/13/2019] [Accepted: 02/15/2019] [Indexed: 01/27/2023]
Abstract
In humans, mutations in the Disrupted-in-schizophrenia 1 (DISC1) gene have been related to psychiatric disorders, including symptoms of abnormal cognitive and emotional behaviors. In our previous studies, overexpression of the human DISC1 gene in rats resulted in schizophrenia-like phenotypes showing deficits in motor learning, impaired cognitive function and dysfunctions of the dopamine system. Here we asked, whether the DISC1 overexpression affects locomotor activity in the open field (OF), anxiety in the elevated plus-maze (EPM), depression-related behavior in the forced swim test (FST), and attention-like/short-term working-memory in the spontaneous alternation behavior (SAB) in the T-maze in transgenic DISC1 (tgDISC1) rats and littermate controls (WT). TgDISC1 rats showed enhanced anxiety behavior in the EPM and an impairment in attention-like/short-term working-memory in the SAB. However, tgDISC1 animals showed no locomotor impairments or depression-like behavior in the OF and FST. These results suggest that DISC1 overexpression leads to higher anxiety level and an attention-like/working-memory deficit. These findings may expand the causal role of DISC1 in its contribution to multiple symptom dimensions of psychiatric disorders.
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Affiliation(s)
- An-Li Wang
- Center for Behavioral Neuroscience, Institute of Experimental Psychology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
| | - Owen Y Chao
- Center for Behavioral Neuroscience, Institute of Experimental Psychology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Department of Biomedical Sciences, School of Medicine, University of Minnesota, Duluth, MN, USA.
| | - Yi-Mei Yang
- Department of Biomedical Sciences, School of Medicine, University of Minnesota, Duluth, MN, USA.
| | - Svenja V Trossbach
- Department Neuropathology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
| | - Christian P Müller
- Department of Psychiatry and Psychotherapy, University Hospital, Friedrich-Alexander-University Erlangen-Nuremberg, Schwabachanlage 6, 91054 Erlangen, Germany.
| | - Carsten Korth
- Department Neuropathology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
| | - Joseph P Huston
- Center for Behavioral Neuroscience, Institute of Experimental Psychology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
| | - Maria Angelica de Souza Silva
- Center for Behavioral Neuroscience, Institute of Experimental Psychology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
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